Three-dimensional information processing method and three-dimensional information processing device

ABSTRACT

A three-dimensional information processing method includes: obtaining, via a communication channel, map data that includes first three-dimensional position information; generating second three-dimensional position information from information detected by a sensor; judging whether one of the first three-dimensional position information and the second three-dimensional position information is abnormal by performing, on one of the first three-dimensional position information and the second three-dimensional position information, a process of judging whether an abnormality is present; determining a coping operation to cope with the abnormality when one of the first three-dimensional position information and the second three-dimensional position information is judged to be abnormal; and executing a control that is required to perform the coping operation.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a U.S. continuation application of PCT InternationalPatent Application Number PCT/JP2017/030034 filed on Aug. 23, 2017,claiming the benefit of priority of U.S. Provisional Patent ApplicationNo. 62/379,878 filed on Aug. 26, 2016, the entire contents of which arehereby incorporated by reference.

BACKGROUND 1. Technical Field

The present disclosure relates to a three-dimensional informationprocessing method and a three-dimensional information processing device.

2. Description of the Related Art

Devices or services utilizing three-dimensional data are expected tofind their widespread use in a wide range of fields, such as computervision that enables autonomous operations of cars or robots, mapinformation, monitoring, infrastructure inspection, and videodistribution. Three-dimensional data is obtained through various meansincluding a distance sensor such as a rangefinder, as well as a stereocamera and a combination of a plurality of monocular cameras.

Methods of representing three-dimensional data include a method known asa point cloud scheme that represents the shape of a three-dimensionalstructure by a point group in a three-dimensional space (for example,see “Octree-Based Progressive Geometry Coding of Point Clouds”,Eurographics Symposium on Point-Based Graphics (2006)). In the pointcloud scheme, the positions and colors of a point group are stored.While point cloud is expected to be a mainstream method of representingthree-dimensional data, a massive amount of data of a point groupnecessitates compression of the amount of three-dimensional data byencoding for accumulation and transmission, as in the case of atwo-dimensional moving picture (examples include MPEG-4 AVC and HEVCstandardized by MPEG).

Meanwhile, point cloud compression is partially supported by, forexample, an open-source library (Point Cloud Library) for pointcloud-related processing.

SUMMARY

A three-dimensional information processing method or a three-dimensionalinformation processing device that processes such three-dimensionalinformation is awaited to appropriately cope with an abnormalityregarding three-dimensional position information in the event of itsoccurrence.

The present disclosure aims to provide a three-dimensional informationprocessing method or a three-dimensional information processing devicecapable of appropriately coping with an abnormality regardingthree-dimensional position information in the event of its occurrence.

The three-dimensional information processing method according to oneaspect of the present disclosure includes: obtaining, via acommunication channel, map data that includes first three-dimensionalposition information; generating second three-dimensional positioninformation from information detected by a sensor; judging whether oneof the first three-dimensional position information and the secondthree-dimensional position information is abnormal by performing, on oneof the first three-dimensional position information and the secondthree-dimensional position information, a process of judging whether anabnormality is present; determining a coping operation to cope with theabnormality when one of the first three-dimensional position informationand the second three-dimensional position information is judged to beabnormal; and executing a control that is required to perform the copingoperation.

Note that these general or specific aspects may be implemented as asystem, a method, an integrated circuit, a computer program, or acomputer-readable recording medium such as a CD-ROM, or may beimplemented as an any combination of a system, a method, an integratedcircuit, a computer program, and a recording medium.

The present disclosure is capable of providing a three-dimensionalinformation processing method or a three-dimensional informationprocessing device that copes with an abnormality regardingthree-dimensional position information in the event of its occurrence.

BRIEF DESCRIPTION OF DRAWINGS

These and other objects, advantages and features of the disclosure willbecome apparent from the following description thereof taken inconjunction with the accompanying drawings that illustrate a specificembodiment of the present disclosure.

FIG. 1 is a diagram showing the structure of encoded three-dimensionaldata according to Embodiment 1;

FIG. 2 is a diagram showing an example of prediction structures amongSPCs that belong to the lowermost layer in a GOS according to Embodiment1;

FIG. 3 is a diagram showing an example of prediction structures amonglayers according to Embodiment 1;

FIG. 4 is a diagram showing an example order of encoding GOSs accordingto Embodiment 1;

FIG. 5 is a diagram showing an example order of encoding GOSs accordingto Embodiment 1;

FIG. 6 is a block diagram of a three-dimensional data encoding deviceaccording to Embodiment 1;

FIG. 7 is a flowchart of encoding processes according to Embodiment 1;

FIG. 8 is a block diagram of a three-dimensional data decoding deviceaccording to Embodiment 1;

FIG. 9 is a flowchart of decoding processes according to Embodiment 1;

FIG. 10 is a diagram showing an example of meta information according toEmbodiment 1;

FIG. 11 is a diagram showing an example structure of a SWLD according toEmbodiment 2;

FIG. 12 is a diagram showing example operations performed by a serverand a client according to Embodiment 2;

FIG. 13 is a diagram showing example operations performed by the serverand a client according to Embodiment 2;

FIG. 14 is a diagram showing example operations performed by the serverand the clients according to Embodiment 2;

FIG. 15 is a diagram showing example operations performed by the serverand the clients according to Embodiment 2;

FIG. 16 is a block diagram of a three-dimensional data encoding deviceaccording to Embodiment 2;

FIG. 17 is a flowchart of encoding processes according to Embodiment 2;

FIG. 18 is a block diagram of a three-dimensional data decoding deviceaccording to Embodiment 2;

FIG. 19 is a flowchart of decoding processes according to Embodiment 2;

FIG. 20 is a diagram showing an example structure of a WLD according toEmbodiment 2;

FIG. 21 is a diagram showing an example octree structure of the WLDaccording to Embodiment 2;

FIG. 22 is a diagram showing an example structure of a SWLD according toEmbodiment 2;

FIG. 23 is a diagram showing an example octree structure of the SWLDaccording to Embodiment 2;

FIG. 24 is a schematic diagram showing three-dimensional data beingtransmitted/received between vehicles according to Embodiment 3;

FIG. 25 is a diagram showing an example of three-dimensional datatransmitted between vehicles according to Embodiment 3;

FIG. 26 is a block diagram of a three-dimensional data creation deviceaccording to Embodiment 3;

FIG. 27 is a flowchart of the processes of creating three-dimensionaldata according to Embodiment 3;

FIG. 28 is a block diagram of a three-dimensional data transmissiondevice according to Embodiment 3;

FIG. 29 is a flowchart of the processes of transmittingthree-dimensional data according to Embodiment 3;

FIG. 30 is a block diagram of a three-dimensional data creation deviceaccording to Embodiment 3;

FIG. 31 is a flowchart of the processes of creating three-dimensionaldata according to Embodiment 3;

FIG. 32 is a block diagram of a three-dimensional data transmissiondevice according to Embodiment 3;

FIG. 33 is a flowchart of the processes of transmittingthree-dimensional data according to Embodiment 3;

FIG. 34 is a block diagram of a three-dimensional information processingdevice according to Embodiment 4;

FIG. 35 is a flowchart of a three-dimensional information processingmethod according to Embodiment 4;

FIG. 36 is a flowchart of a three-dimensional information processingmethod according to Embodiment 4;

FIG. 37 illustrates a configuration of a video information processingsystem;

FIG. 38 illustrates one example of a notification screen displayed whena camera is activated;

FIG. 39 illustrates an overall configuration of a content providingsystem that implements content distribution services;

FIG. 40 illustrates an overall configuration of a digital broadcastingsystem;

FIG. 41 illustrates one example of a smartphone; and

FIG. 42 is a block diagram illustrating an example of a configuration ofa smartphone.

DETAILED DESCRIPTION OF THE EMBODIMENTS

While the use of encoded data such as that of a point cloud in an actualdevice or service requires random access to a desired spatial positionor object, there has been no functionality for random access in encodedthree-dimensional data, nor an encoding method therefor.

The present disclosure describes a three-dimensional data encodingmethod, a three-dimensional data decoding method, a three-dimensionaldata encoding device, or a three-dimensional data decoding devicecapable of providing random access functionality for encodedthree-dimensional data.

The three-dimensional data encoding method according to one aspect ofthe present disclosure is a three-dimensional data encoding method forencoding three-dimensional data, the method including: dividing thethree-dimensional data into first processing units, each being a randomaccess unit and being associated with three-dimensional coordinates; andencoding each of the first processing units to generate encoded data.

This enables random access on a first processing unit basis. Thethree-dimensional data encoding method is thus capable of providingrandom access functionality for encoded three-dimensional data.

For example, the three-dimensional data encoding method may includegenerating first information indicating the first processing units andthe three-dimensional coordinates associated with each of the firstprocessing units, and the encoded data may include the firstinformation.

For example, the first information may further indicate at least one ofan object, a time, and a data storage location that are associated witheach of the first processing units.

For example, in the dividing, each of the first processing units may befurther divided into second processing units, and in the encoding, eachof the second processing units may be encoded.

For example, in the encoding, a current second processing unit among thesecond processing units included in a current first processing unitamong the first processing units may be encoded by referring to anotherof the second processing units included in the current first processingunit.

With this, the encoding efficiency is increased by referring to anothersecond processing unit.

For example, in the encoding, one of three types may be selected as atype of the current second processing unit, and the current secondprocessing unit may be encoded in accordance with the type that has beenselected, the three types being a first type in which another of thesecond processing units is not referred to, a second type in whichanother of the second processing units is referred to, and a third typein which other two of the second processing units are referred to.

For example, in the encoding, a frequency of selecting the first typemay be changed in accordance with the number, or sparseness anddenseness of objects included in the three-dimensional data.

This enables an adequate setting of random accessibility and encodingefficiency, which are in a tradeoff relationship.

For example, in the encoding, a size of the first processing units maybe determined in accordance with the number, or sparseness and densenessof objects or dynamic objects included in the three-dimensional data.

This enables an adequate setting of random accessibility and encodingefficiency, which are in a tradeoff relationship.

For example, each of the first processing units may be spatially dividedin a predetermined direction to have layers, each including at least oneof the second processing units, and in the encoding, each of the secondprocessing units may be encoded by referring to another of the secondprocessing units included in an identical layer of the each of thesecond processing units or included in a lower layer of the identicallayer.

This achieves an increased random accessibility to an important layer ina system, while preventing a decrease in the encoding efficiency.

For example, in the dividing, among the second processing units, asecond processing unit including only a static object and a secondprocessing unit including only a dynamic object may be assigned todifferent ones of the first processing units.

This enables easy control of dynamic objects and static objects.

For example, in the encoding, dynamic objects may be individuallyencoded, and encoded data of each of the dynamic objects may beassociated with a second processing unit, among the second processingunits, that includes only a static object.

This enables easy control of dynamic objects and static objects.

For example, in the dividing, each of the second processing units may befurther divided into third processing units, and in the encoding, eachof the third processing units may be encoded.

For example, each of the third processing units may include at least onevoxel, which is a minimum unit in which position information isassociated.

For example, each of the second processing units may include a keypointgroup derived from information obtained by a sensor.

For example, the encoded data may include information indicating anencoding order of the first processing units.

For example, the encoded data may include information indicating a sizeof the first processing units.

For example, in the encoding, the first processing units may be encodedin parallel.

Also, the three-dimensional data decoding method according anotheraspect of the present disclosure is a three-dimensional data decodingmethod for decoding three-dimensional data, the method including:decoding each encoded data of first processing units, each being arandom access unit and being associated with three-dimensionalcoordinates, to generate three-dimensional data of the first processingunits.

This enables random access on a first processing unit basis. Thethree-dimensional data decoding method is thus capable of providingrandom access functionality for encoded three-dimensional data.

Also, the three-dimensional data encoding device according to stillanother aspect of the present disclosure is a three-dimensional dataencoding device that encodes three-dimensional data that may include: adivider that divides the three-dimensional data into first processingunits, each being a random access unit and being associated withthree-dimensional coordinates; and an encoder that encodes each of thefirst processing units to generate encoded data.

This enables random access on a first processing unit basis. Thethree-dimensional data encoding device is thus capable of providingrandom access functionality for encoded three-dimensional data.

Also, the three-dimensional data decoding device according to stillanother aspect of the present disclosure is a three-dimensional datadecoding device that decodes three-dimensional data that may include: adecoder that decodes each encoded data of first processing units, eachbeing a random access unit and being associated with three-dimensionalcoordinates, to generate three-dimensional data of the first processingunits.

This enables random access on a first processing unit basis. Thethree-dimensional data decoding device is thus capable of providingrandom access functionality for encoded three-dimensional data.

Note that the present disclosure, which is configured to divide a spacefor encoding, enables quantization, prediction, etc. of such space, andthus is effective also for the case where no random access is performed.

Also, the three-dimensional data encoding method according to one aspectof the present disclosure includes: extracting, from firstthree-dimensional data, second three-dimensional data having an amountof a feature greater than or equal to a threshold; and encoding thesecond three-dimensional data to generate first encodedthree-dimensional data.

According to this three-dimensional data encoding method, first encodedthree-dimensional data is generated that is obtained by encoding datahaving an amount of a feature greater than or equal to the threshold.This reduces the amount of encoded three-dimensional data compared tothe case where the first three-dimensional data is encoded as it is. Thethree-dimensional data encoding method is thus capable of reducing theamount of data to be transmitted.

For example, the three-dimensional data encoding method may furtherinclude encoding the first three-dimensional data to generate secondencoded three-dimensional data.

This three-dimensional data encoding method enables selectivetransmission of the first encoded three-dimensional data and the secondencoded three-dimensional data, in accordance, for example, with theintended use, etc.

For example, the second three-dimensional data may be encoded by a firstencoding method, and the first three-dimensional data may be encoded bya second encoding method different from the first encoding method.

This three-dimensional data encoding method enables the use of anencoding method suitable for each of the first three-dimensional dataand the second three-dimensional data.

For example, of intra prediction and inter prediction, the interprediction may be more preferentially performed in the first encodingmethod than in the second encoding method.

This three-dimensional data encoding method enables inter prediction tobe more preferentially performed on the second three-dimensional data inwhich adjacent data items are likely to have low correlation.

For example, the first encoding method and the second encoding methodmay represent three-dimensional positions differently.

This three-dimensional data encoding method enables the use of a moresuitable method to represent three-dimensional positions ofthree-dimensional data in consideration of the difference in the numberof data items included.

For example, at least one of the first encoded three-dimensional dataand the second encoded three-dimensional data may include an identifierindicating whether the at least one of the first encodedthree-dimensional data and the second encoded three-dimensional data isencoded three-dimensional data obtained by encoding the firstthree-dimensional data or encoded three-dimensional data obtained byencoding part of the first three-dimensional data.

This enables the decoding device to readily judge whether the obtainedencoded three-dimensional data is the first encoded three-dimensionaldata or the second encoded three-dimensional data.

For example, in the encoding of the second three-dimensional data, thesecond three-dimensional data may be encoded in a manner that the firstencoded three-dimensional data has a smaller data amount than a dataamount of the second encoded three-dimensional data.

This three-dimensional data encoding method enables the first encodedthree-dimensional data to have a smaller data amount than the dataamount of the second encoded three-dimensional data.

For example, in the extracting, data corresponding to an object having apredetermined attribute may be further extracted from the firstthree-dimensional data as the second three-dimensional data.

This three-dimensional data encoding method is capable of generating thefirst encoded three-dimensional data that includes data required by thedecoding device.

For example, the three-dimensional data encoding method may furtherinclude sending, to a client, one of the first encoded three-dimensionaldata and the second encoded three-dimensional data in accordance with astatus of the client.

This three-dimensional data encoding method is capable of sendingappropriate data in accordance with the status of the client.

For example, the status of the client may include one of a communicationcondition of the client and a traveling speed of the client.

For example, the three-dimensional data encoding method may furtherinclude sending, to a client, one of the first encoded three-dimensionaldata and the second encoded three-dimensional data in accordance with arequest from the client.

This three-dimensional data encoding method is capable of sendingappropriate data in accordance with the request from the client.

Also, the three-dimensional data decoding method according to anotheraspect of the present disclosure includes: decoding, by a first decodingmethod, first encoded three-dimensional data obtained by encoding secondthree-dimensional data having an amount of a feature greater than orequal to a threshold, the second three-dimensional data having beenextracted from first three-dimensional data; and decoding, by a seconddecoding method, second encoded three-dimensional data obtained byencoding the first three-dimensional data, the second decoding methodbeing different from the first decoding method.

This three-dimensional data decoding method enables selective receptionof the first encoded three-dimensional data obtained by encoding datahaving an amount of a feature greater than or equal to the threshold andthe second encoded three-dimensional data, in accordance, for example,with the intended use, etc. The three-dimensional data decoding methodis thus capable of reducing the amount of data to be transmitted. Suchthree-dimensional data decoding method further enables the use of adecoding method suitable for each of the first three-dimensional dataand the second three-dimensional data.

For example, of intra prediction and inter prediction, the interprediction may be more preferentially performed in the first decodingmethod than in the second decoding method.

This three-dimensional data decoding method enables inter prediction tobe more preferentially performed on the second three-dimensional data inwhich adjacent data items are likely to have low correlation.

For example, the first decoding method and the second decoding methodmay represent three-dimensional positions differently.

This three-dimensional data decoding method enables the use of a moresuitable method to represent three-dimensional positions ofthree-dimensional data in consideration of the difference in the numberof data items included.

For example, at least one of the first encoded three-dimensional dataand the second encoded three-dimensional data may include an identifierindicating whether the at least one of the first encodedthree-dimensional data and the second encoded three-dimensional data isencoded three-dimensional data obtained by encoding the firstthree-dimensional data or encoded three-dimensional data obtained byencoding part of the first three-dimensional data, and the identifiermay be referred to in identifying between the first encodedthree-dimensional data and the second encoded three-dimensional data.

This enables judgment to be readily made of whether the obtained encodedthree-dimensional data is the first encoded three-dimensional data orthe second encoded three-dimensional data.

For example, the three-dimensional data decoding method may furtherinclude: notifying a server of a status of a client; and receiving oneof the first encoded three-dimensional data and the second encodedthree-dimensional data from the server, in accordance with the status ofthe client.

This three-dimensional data decoding method is capable of receivingappropriate data in accordance with the status of the client.

For example, the status of the client may include one of a communicationcondition of the client and a traveling speed of the client.

For example, the three-dimensional data decoding method may furtherinclude: making a request of a server for one of the first encodedthree-dimensional data and the second encoded three-dimensional data;and receiving one of the first encoded three-dimensional data and thesecond encoded three-dimensional data from the server, in accordancewith the request.

This three-dimensional data decoding method is capable of receivingappropriate data in accordance with the intended use.

Also, the three-dimensional data encoding device according to stillanother aspect of the present disclosure include: an extractor thatextracts, from first three-dimensional data, second three-dimensionaldata having an amount of a feature greater than or equal to a threshold;and a first encoder that encodes the second three-dimensional data togenerate first encoded three-dimensional data.

This three-dimensional data encoding device generates first encodedthree-dimensional data by encoding data having an amount of a featuregreater than or equal to the threshold. This reduces the amount datacompared to the case where the first three-dimensional data is encodedas it is. The three-dimensional data encoding device is thus capable ofreducing the amount of data to be transmitted.

Also, the three-dimensional data decoding device according to stillanother aspect of the present disclosure includes: a first decoder thatdecodes, by a first decoding method, first encoded three-dimensionaldata obtained by encoding second three-dimensional data having an amountof a feature greater than or equal to a threshold, the secondthree-dimensional data having been extracted from firstthree-dimensional data; and a second decoder that decodes, by a seconddecoding method, second encoded three-dimensional data obtained byencoding the first three-dimensional data, the second decoding methodbeing different from the first decoding method.

This three-dimensional data decoding devices enables selective receptionof the first encoded three-dimensional data obtained by encoding datahaving an amount of a feature greater than or equal to the threshold andthe second encoded three-dimensional data, in accordance, for example,with the intended use, etc. The three-dimensional data decoding deviceis thus capable of reducing the amount of data to be transmitted. Suchthree-dimensional data decoding device further enables the use of adecoding method suitable for each of the first three-dimensional dataand the second three-dimensional data.

Also, the three-dimensional data creation method according to one aspectof the present disclosure includes: creating first three-dimensionaldata from information detected by a sensor; receiving encodedthree-dimensional data that is obtained by encoding secondthree-dimensional data; decoding the encoded three-dimensional data thathas been received to obtain the second three-dimensional data; andmerging the first three-dimensional data with the secondthree-dimensional data to create third three-dimensional data.

Such three-dimensional data creation method is capable of creatingdetailed three-dimensional data by use of the created firstthree-dimensional data and the received second three-dimensional data.

For example, in the merging, the first three-dimensional data may bemerged with the second three-dimensional data to create the thirdthree-dimensional data that is denser than the first three-dimensionaldata and the second three-dimensional data.

For example, the second three-dimensional data may be three-dimensionaldata that is generated by extracting, from fourth three-dimensionaldata, data having an amount of a feature greater than or equal to athreshold.

Such three-dimensional data creation method reduces the amount ofthree-dimensional data to be transmitted.

For example, the three-dimensional data creation method may furtherinclude searching for a transmission device that transmits the encodedthree-dimensional data, and in the receiving, the encodedthree-dimensional data may be received from the transmission device thathas been searched out.

Such three-dimensional data creation method is, for example, capable ofsearching for a transmission device having necessary three-dimensionaldata.

For example, the three-dimensional data creation method may furtherinclude: determining a request range that is a range of athree-dimensional space, three-dimensional data of which is requested;and transmitting information indicating the request range to thetransmission device, wherein the second three-dimensional data mayinclude the three-dimensional data of the request range.

Such three-dimensional data creation method is capable of receivingnecessary three-dimensional data, while reducing the amount ofthree-dimensional data to be transmitted.

For example, in the determining, a spatial range that includes anocclusion region undetectable by the sensor may be determined as therequest range.

The three-dimensional data transmission method according to anotheraspect of the present disclosure includes: creating fifththree-dimensional data from information detected by a sensor; extractingpart of the fifth three-dimensional data to create sixththree-dimensional data; encoding the sixth three-dimensional data togenerate encoded three-dimensional data; and transmitting the encodedthree-dimensional data.

Such three-dimensional data transmission method is capable oftransmitting self-created three-dimensional data to another device,while reducing the amount of three-dimensional data to be transmitted.

For example, in the creating, the fifth three-dimensional data may becreated by creating seventh three-dimensional data from the informationdetected by the sensor, and by extracting data having an amount of afeature greater than or equal to a threshold from the sevenththree-dimensional data.

Such three-dimensional data transmission method reduces the amount ofthree-dimensional data to be transmitted.

For example, the three-dimensional data transmission method may furtherinclude: receiving, from a reception device, information indicating arequest range that is a range of a three-dimensional space,three-dimensional data of which is requested, wherein in the extracting,the sixth three-dimensional data may be created by extracting thethree-dimensional data of the request range from the fifththree-dimensional data, and in the transmitting, the encodedthree-dimensional data may be transmitted to the reception device.

Such three-dimensional data transmission method reduces the amount ofthree-dimensional data to be transmitted.

Also, the three-dimensional data creation device according to stillanother aspect of the present disclosure includes: a creator thatcreates first three-dimensional data from information detected by asensor; a receiver that receives encoded three-dimensional data that isobtained by encoding second three-dimensional data; a decoder thatdecodes the encoded three-dimensional data that has been received toobtain the second three-dimensional data; and a merger that merges thefirst three-dimensional data with the second three-dimensional data tocreate third three-dimensional data.

Such three-dimensional data creation device is capable of creatingdetailed third three-dimensional data by use of the created firstthree-dimensional data and the received second three-dimensional data.

Also, the three-dimensional data transmission device according to stillanother aspect of the present disclosure includes: a creator thatcreates fifth three-dimensional data from information detected by asensor; an extractor that extracts part of the fifth three-dimensionaldata to create sixth three-dimensional data; an encoder that encodes thesixth three-dimensional data to generate encoded three-dimensional data;and a transmitter that transmits the encoded three-dimensional data.

Such three-dimensional data transmission device is capable oftransmitting self-created three-dimensional data to another device,while reducing the amount of three-dimensional data to be transmitted.

Also, the three-dimensional information processing method according oneaspect of the present disclosure includes: obtaining, via acommunication channel, map data that includes first three-dimensionalposition information; generating second three-dimensional positioninformation from information detected by a sensor; judging whether oneof the first three-dimensional position information and the secondthree-dimensional position information is abnormal by performing, on oneof the first three-dimensional position information and the secondthree-dimensional position information, a process of judging whether anabnormality is present; determining a coping operation to cope with theabnormality when one of the first three-dimensional position informationand the second three-dimensional position information is judged to beabnormal; and executing a control that is required to perform the copingoperation.

Such three-dimensional information processing method is capable ofdetecting an abnormality regarding one of the first three-dimensionalposition information and the second three-dimensional positioninformation, and performing a coping operation therefor.

For example, the first three-dimensional position information mayinclude a plurality of random access units, each of which is an assemblyof at least one subspace and is individually decodable, the at least onesubspace having three-dimensional coordinates information and serving asa unit in which each of the plurality of random access units is encoded.

Such three-dimensional information processing method is capable ofreducing the data amount of the first three-dimensional positioninformation to be obtained.

For example, the first three-dimensional position information may bedata obtained by encoding keypoints, each of which has an amount of athree-dimensional feature greater than or equal to a predeterminedthreshold.

Such three-dimensional information processing method is capable ofreducing the data amount of the first three-dimensional positioninformation to be obtained.

For example, the judging may include judging whether the firstthree-dimensional position information is obtainable via thecommunication channel, and when the first three-dimensional positioninformation is unobtainable via the communication channel, judging thefirst three-dimensional position information to be abnormal.

Such three-dimensional information processing method is capable ofperforming an appropriate coping operation in accordance withcommunication conditions, etc., when the first three-dimensionalposition information is unobtainable.

For example, the three-dimensional information processing method mayfurther include: estimating a location of a mobile object having thesensor by use of the first three-dimensional position information andthe second three-dimensional position information. The judging mayinclude predicting whether the mobile object will enter an area in whichcommunication conditions are poor. In the executing of the control, themobile object may obtain the first three-dimensional positioninformation before entering the area in which the communicationconditions are poor, when the mobile object is predicted to enter thearea.

Such three-dimensional information processing method is capable ofobtaining the first three-dimensional position information in advance,when there is a possibility that the first three-dimensional positioninformation may be unobtainable.

For example, the executing of the control may include obtaining, via thecommunication channel, third three-dimensional position informationhaving a narrower range than a range of the first three-dimensionalposition information, when the first three-dimensional positioninformation is unobtainable via the communication channel.

Such three-dimensional information processing method is capable ofreducing the data amount of data to be obtained via a communicationchannel, thereby obtaining the three-dimensional position informationeven when communication conditions are poor.

For example, the three-dimensional information processing method mayfurther include: estimating a location of a mobile object having thesensor by use of the first three-dimensional position information andthe second three-dimensional position information. The executing of thecontrol may include obtaining, via the communication channel, map dataincluding two-dimensional position information, when the firstthree-dimensional position information is unobtainable via thecommunication channel, and estimating the location of the mobile objecthaving the sensor by use of the two-dimensional position information andthe second three-dimensional position information.

Such three-dimensional information processing method is capable ofreducing the data amount of data to be obtained via a communicationchannel, thereby obtaining the three-dimensional position informationeven when communication conditions are poor.

For example, the three-dimensional information processing method mayfurther include: performing automatic operation of the mobile object byuse of the location having been estimated. The judging may furtherinclude judging whether to perform the automatic operation of the mobileobject by use of the location of the mobile object, based on anenvironment in which the mobile object is traveling, the location havingbeen estimated by use of the two-dimensional position information andthe second three-dimensional position information.

Such three-dimensional information processing method is capable ofjudging whether to continue automatic operation, in accordance with anenvironment in which the mobile object is traveling.

For example, the three-dimensional information processing method mayfurther include: performing automatic operation of the mobile object byuse of the location having been estimated. The executing of the controlmay include switching a mode of the automatic operation to another basedon an environment in which the mobile object is traveling.

Such three-dimensional information processing method is capable ofsetting an appropriate automatic operation mode, in accordance with anenvironment in which the mobile object is traveling.

For example, the judging may include judging whether the firstthree-dimensional position information has integrity, and when the firstthree-dimensional position information has no integrity, judging thefirst three-dimensional position information to be abnormal.

Such three-dimensional information processing method is capable ofperforming an appropriate coping operation, when, for example, the firstthree-dimensional position information is corrupt.

For example, the judging may include judging whether a data accuracy ishigher than or equal to a reference value, and when the data accuracy isnot higher than or equal to the reference value, judging the secondthree-dimensional position information to be abnormal, the data accuracybeing an accuracy of the second three-dimensional position informationhaving been generated.

Such three-dimensional information processing method is capable ofperforming an appropriate coping operation, when the accuracy of thesecond three-dimensional position information is low.

For example, the executing of the control may include generating fourththree-dimensional position information from information detected by analternative sensor different from the sensor, when the data accuracy ofthe second three-dimensional position information having been generatedis not higher than or equal to the reference value.

Such three-dimensional information processing method is capable ofobtaining three-dimensional position information by use of analternative sensor, when, for example, the sensor has trouble.

For example, the three-dimensional information processing method mayfurther include: estimating a location of a mobile object having thesensor by use of the first three-dimensional position information andthe second three-dimensional position information; and performingautomatic operation of the mobile object by use of the location havingbeen estimated. The executing of the control may include switching amode of the automatic operation to another when the data accuracy of thesecond three-dimensional position information having been generated isnot higher than or equal to the reference value.

Such three-dimensional information processing method is capable ofperforming an appropriate coping operation, when the accuracy of thesecond three-dimensional position information is low.

For example, the executing of the control may include calibrating anoperation of the sensor, when the data accuracy of the secondthree-dimensional position information having been generated is nothigher than or equal to the reference value.

Such three-dimensional information processing method is capable ofincreasing the accuracy of the second three-dimensional positioninformation, when the accuracy of the second three-dimensional positioninformation is low.

Also, the three-dimensional information processing device according toanother aspect of the present disclosure includes: an obtainer thatobtains, via a communication channel, map data that includes firstthree-dimensional position information; a generator that generatessecond three-dimensional position information from information detectedby a sensor; a judgment unit that judges whether one of the firstthree-dimensional position information and the second three-dimensionalposition information is abnormal by performing, on one of the firstthree-dimensional position information and the second three-dimensionalposition information, a process of judging whether an abnormality ispresent; a determiner that determines a coping operation to cope withthe abnormality when one of the first three-dimensional positioninformation and the second three-dimensional position information isjudged to be abnormal; and an operation controller that executes acontrol required to perform the coping operation.

Such three-dimensional information processing device is capable ofdetecting an abnormality regarding one of the first three-dimensionalposition information and the second three-dimensional positioninformation, and performing a coping operation therefor.

Note that these general or specific aspects may be implemented as asystem, a method, an integrated circuit, a computer program, or acomputer-readable recording medium such as a CD-ROM, or may beimplemented as an any combination of a system, a method, an integratedcircuit, a computer program, and a recording medium.

The following describes embodiments with reference to the drawings. Notethat the following embodiments show exemplary embodiments of the presentdisclosure. The numerical values, shapes, materials, structuralcomponents, the arrangement and connection of the structural components,steps, the processing order of the steps, etc. shown in the followingembodiments are mere examples, and thus are not intended to limit thepresent disclosure. Of the structural components described in thefollowing embodiments, structural components not recited in any one ofthe independent claims that indicate the broadest concepts will bedescribed as optional structural components.

Embodiment 1

First, the data structure of encoded three-dimensional data (hereinafteralso referred to as encoded data) according to the present embodimentwill be described. FIG. 1 is a diagram showing the structure of encodedthree-dimensional data according to the present embodiment.

In the present embodiment, a three-dimensional space is divided intospaces (SPCs), which correspond to pictures in moving picture encoding,and the three-dimensional data is encoded on a SPC-by-SPC basis. EachSPC is further divided into volumes (VLMs), which correspond tomacroblocks, etc. in moving picture encoding, and predictions andtransforms are performed on a VLM-by-VLM basis. Each volume includes aplurality of voxels (VXLs), each being a minimum unit in which positioncoordinates are associated. Note that prediction is a process ofgenerating predictive three-dimensional data analogous to a currentprocessing unit by referring to another processing unit, and encoding adifferential between the predictive three-dimensional data and thecurrent processing unit, as in the case of predictions performed ontwo-dimensional images. Such prediction includes not only spatialprediction in which another prediction unit corresponding to the sametime is referred to, but also temporal prediction in which a predictionunit corresponding to a different time is referred to.

When encoding a three-dimensional space represented by point group datasuch as a point cloud, for example, the three-dimensional data encodingdevice (hereinafter also referred to as the encoding device) encodes thepoints in the point group or points included in the respective voxels ina collective manner, in accordance with a voxel size. Finer voxelsenable a highly-precise representation of the three-dimensional shape ofa point group, while larger voxels enable a rough representation of thethree-dimensional shape of a point group.

Note that the following describes the case where three-dimensional datais a point cloud, but three-dimensional data is not limited to a pointcloud, and thus three-dimensional data of any format may be employed.

Also note that voxels with a hierarchical structure may be used. In sucha case, when the hierarchy includes n levels, whether a sampling pointis included in the n−1th level or its lower levels (the lower levels ofthe n-th level) may be sequentially indicated. For example, when onlythe n-th level is decoded, and the n−1th level or its lower levelsinclude a sampling point, the n-th level can be decoded on theassumption that a sampling point is included at the center of a voxel inthe n-th level.

Also, the encoding device obtains point group data, using, for example,a distance sensor, a stereo camera, a monocular camera, a gyroscopesensor, or an inertial sensor.

As in the case of moving picture encoding, each SPC is classified intoone of at least the three prediction structures that include: intra SPC(I-SPC), which is individually decodable; predictive SPC (P-SPC) capableof only a unidirectional reference; and bidirectional SPC (B-SPC)capable of bidirectional references. Each SPC includes two types of timeinformation: decoding time and display time.

Furthermore, as shown in FIG. 1, a processing unit that includes aplurality of SPCs is a group of spaces (GOS), which is a random accessunit. Also, a processing unit that includes a plurality of GOSs is aworld (WLD). The spatial region occupied by each world is associatedwith an absolute position on earth, by use of, for example, GPS, orlatitude and longitude information. Such position information is storedas meta-information. Note that meta-information may be included inencoded data, or may be transmitted separately from the encoded data.

Also, inside a GOS, all SPCs may be three-dimensionally adjacent to oneanother, or there may be a SPC that is not three-dimensionally adjacentto another SPC.

Note that the following also describes processes such as encoding,decoding, and reference to be performed on three-dimensional dataincluded in processing units such as GOS, SPC, and VLM, simply asperforming encoding/to encode, decoding/to decode, referring to, etc. ona processing unit. Also note that three-dimensional data included in aprocessing unit includes, for example, at least one pair of a spatialposition such as three-dimensional coordinates and an attribute valuesuch as color information.

Next, the prediction structures among SPCs in a GOS will be described. Aplurality of SPCs in the same GOS or a plurality of VLMs in the same SPCoccupy mutually different spaces, while having the same time information(the decoding time and the display time).

A SPC in a GOS that comes first in the decoding order is an I-SPC. GOSscome in two types: closed GOS and open GOS. A closed GOS is a GOS inwhich all SPCs in the GOS are decodable when decoding starts from thefirst I-SPC. Meanwhile, an open GOS is a GOS in which a different GOS isreferred to in one or more SPCs preceding the first I-SPC in the GOS inthe display time, and thus cannot be singly decoded.

Note that in the case of encoded data of map information, for example, aWLD is sometimes decoded in the backward direction, which is opposite tothe encoding order, and thus backward reproduction is difficult whenGOSs are interdependent. In such a case, a closed GOS is basically used.

Each GOS has a layer structure in height direction, and SPCs aresequentially encoded or decoded from SPCs in the bottom layer.

FIG. 2 is a diagram showing an example of prediction structures amongSPCs that belong to the lowermost layer in a GOS. FIG. 3 is a diagramshowing an example of prediction structures among layers.

A GOS includes at least one I-SPC. Of the objects in a three-dimensionalspace, such as a person, an animal, a car, a bicycle, a signal, and abuilding serving as a landmark, a small-sized object is especiallyeffective when encoded as an I-SPC. When decoding a GOS at a lowthroughput or at a high speed, for example, the three-dimensional datadecoding device (hereinafter also referred to as the decoding device)decodes only I-SPC(s) in the GOS.

The encoding device may also change the encoding interval or theappearance frequency of I-SPCs, depending on the degree of sparsenessand denseness of the objects in a WLD.

In the structure shown in FIG. 3, the encoding device or the decodingdevice encodes or decodes a plurality of layers sequentially from thebottom layer (layer 1). This increases the priority of data on theground and its vicinity, which involve a larger amount of information,when, for example, a self-driving car is concerned.

Regarding encoded data used for a drone, for example, encoding ordecoding may be performed sequentially from SPCs in the top layer in aGOS in height direction.

The encoding device or the decoding device may also encode or decode aplurality of layers in a manner that the decoding device can have arough grasp of a GOS first, and then the resolution is graduallyincreased. The encoding device or the decoding device may performencoding or decoding in the order of layers 3, 8, 1, 9 . . . , forexample.

Next, the handling of static objects and dynamic objects will bedescribed.

A three-dimensional space includes scenes or still objects such as abuilding and a road (hereinafter collectively referred to as staticobjects), and objects with motion such as a car and a person(hereinafter collectively referred to as dynamic objects). Objectdetection is separately performed by, for example, extracting keypointsfrom point cloud data, or from video of a camera such as a stereocamera. In this description, an example method of encoding a dynamicobject will be described.

A first method is a method in which a static object and a dynamic objectare encoded without distinction. A second method is a method in which adistinction is made between a static object and a dynamic object on thebasis of identification information.

For example, a GOS is used as an identification unit. In such a case, adistinction is made between a GOS that includes SPCs constituting astatic object and a GOS that includes SPCs constituting a dynamicobject, on the basis of identification information stored in the encodeddata or stored separately from the encoded data.

Alternatively, a SPC may be used as an identification unit. In such acase, a distinction is made between a SPC that includes VLMsconstituting a static object and a SPC that includes VLMs constituting adynamic object, on the basis of the identification information thusdescribed.

Alternatively, a VLM or a VXL may be used as an identification unit. Insuch a case, a distinction is made between a VLM or a VXL that includesa static object and a VLM or a VXL that includes a dynamic object, onthe basis of the identification information thus described.

The encoding device may also encode a dynamic object as at least one VLMor SPC, and may encode a VLM or a SPC including a static object and aSPC including a dynamic object as mutually different GOSs. When the GOSsize is variable depending on the size of a dynamic object, the encodingdevice separately stores the GOS size as meta-information.

The encoding device may also encode a static object and a dynamic objectseparately from each other, and may superimpose the dynamic object ontoa world constituted by static objects. In such a case, the dynamicobject is constituted by at least one SPC, and each SPC is associatedwith at least one SPC constituting the static object onto which the eachSPC is to be superimposed. Note that a dynamic object may be representednot by SPC(s) but by at least one VLM or VXL.

The encoding device may also encode a static object and a dynamic objectas mutually different streams.

The encoding device may also generate a GOS that includes at least oneSPC constituting a dynamic object. The encoding device may further setthe size of a GOS including a dynamic object (GOS_M) and the size of aGOS including a static object corresponding to the spatial region ofGOS_M at the same size (such that the same spatial region is occupied).This enables superimposition to be performed on a GOS-by-GOS basis.

SPC(s) included in another encoded GOS may be referred to in a P-SPC ora B-SPC constituting a dynamic object. In the case where the position ofa dynamic object temporally changes, and the same dynamic object isencoded as an object in a GOS corresponding to a different time,referring to SPC(s) across GOSs is effective in terms of compressionrate.

The first method and the second method may be selected in accordancewith the intended use of encoded data. When encoded three-dimensionaldata is used as a map, for example, a dynamic object is desired to beseparated, and thus the encoding device uses the second method.Meanwhile, the encoding device uses the first method when the separationof a dynamic object is not required such as in the case wherethree-dimensional data of an event such as a concert and a sports eventis encoded.

The decoding time and the display time of a GOS or a SPC are storable inencoded data or as meta-information. All static objects may have thesame time information. In such a case, the decoding device may determinethe actual decoding time and display time. Alternatively, a differentvalue may be assigned to each GOS or SPC as the decoding time, and thesame value may be assigned as the display time. Furthermore, as in thecase of the decoder model in moving picture encoding such asHypothetical Reference Decoder (HRD) compliant with HEVC, a model may beemployed that ensures that a decoder can perform decoding without failby having a buffer of a predetermined size and by reading a bitstream ata predetermined bit rate in accordance with the decoding times.

Next, the topology of GOSs in a world will be described. The coordinatesof the three-dimensional space in a world are represented by the threecoordinate axes (x axis, y axis, and z axis) that are orthogonal to oneanother. A predetermined rule set for the encoding order of GOSs enablesencoding to be performed such that spatially adjacent GOSs arecontiguous in the encoded data. In an example shown in FIG. 4, forexample, GOSs in the x and z planes are successively encoded. After thecompletion of encoding all GOSs in certain x and z planes, the value ofthe y axis is updated. Stated differently, the world expands in the yaxis direction as the encoding progresses. The GOS index numbers are setin accordance with the encoding order.

Here, the three-dimensional spaces in the respective worlds arepreviously associated one-to-one with absolute geographical coordinatessuch as GPS coordinates or latitude/longitude coordinates.Alternatively, each three-dimensional space may be represented as aposition relative to a previously set reference position. The directionsof the x axis, the y axis, and the z axis in the three-dimensional spaceare represented by directional vectors that are determined on the basisof the latitudes and the longitudes, etc. Such directional vectors arestored together with the encoded data as meta-information.

GOSs have a fixed size, and the encoding device stores such size asmeta-information. The GOS size may be changed depending on, for example,whether it is an urban area or not, or whether it is inside or outsideof a room. Stated differently, the GOS size may be changed in accordancewith the amount or the attributes of objects with information values.Alternatively, in the same world, the encoding device may adaptivelychange the GOS size or the interval between I-SPCs in GOSs in accordancewith the object density, etc. For example, the encoding device sets theGOS size to smaller and the interval between I-SPCs in GOSs to shorter,as the object density is higher.

In an example shown in FIG. 5, to enable random access with a finergranularity, a GOS with a high object density is partitioned into theregions of the third to tenth GOSs. Note that the seventh to tenth GOSsare located behind the third to sixth GOSs.

Next, the structure and the operation flow of the three-dimensional dataencoding device according to the present embodiment will be described.FIG. 6 is a block diagram of three-dimensional data encoding device 100according to the present embodiment. FIG. 7 is a flowchart of an exampleoperation performed by three-dimensional data encoding device 100.

Three-dimensional data encoding device 100 shown in FIG. 6 encodesthree-dimensional data 111, thereby generating encoded three-dimensionaldata 112. Such three-dimensional data encoding device 100 includesobtainer 101, encoding region determiner 102, divider 103, and encoder104.

As shown in FIG. 7, first, obtainer 101 obtains three-dimensional data111, which is point group data (S101).

Next, encoding region determiner 102 determines a current region forencoding from among spatial regions corresponding to the obtained pointgroup data (S102). For example, in accordance with the position of auser or a vehicle, encoding region determiner 102 determines, as thecurrent region, a spatial region around such position.

Next, divider 103 divides the point group data included in the currentregion into processing units. The processing units here means units suchas GOSs and SPCs described above. The current region here correspondsto, for example, a world described above. More specifically, divider 103divides the point group data into processing units on the basis of apredetermined GOS size, or the presence/absence/size of a dynamic object(S103). Divider 103 further determines the starting position of the SPCthat comes first in the encoding order in each GOS.

Next, encoder 104 sequentially encodes a plurality of SPCs in each GOS,thereby generating encoded three-dimensional data 112 (S104).

Note that although an example is described here in which the currentregion is divided into GOSs and SPCs, after which each GOS is encoded,the processing steps are not limited to this order. For example, stepsmay be employed in which the structure of a single GOS is determined,which is followed by the encoding of such GOS, and then the structure ofthe subsequent GOS is determined.

As thus described, three-dimensional data encoding device 100 encodesthree-dimensional data 111, thereby generating encoded three-dimensionaldata 112. More specifically, three-dimensional data encoding device 100divides three-dimensional data into first processing units (GOSs), eachbeing a random access unit and being associated with three-dimensionalcoordinates, divides each of the first processing units (GOSs) intosecond processing units (SPCs), and divides each of the secondprocessing units (SPCs) into third processing units (VLMs). Each of thethird processing units (VLMs) includes at least one voxel (VXL), whichis the minimum unit in which position information is associated.

Next, three-dimensional data encoding device 100 encodes each of thefirst processing units (GOSs), thereby generating encodedthree-dimensional data 112. More specifically, three-dimensional dataencoding device 100 encodes each of the second processing units (SPCs)in each of the first processing units (GOSs). Three-dimensional dataencoding device 100 further encodes each of the third processing units(VLMs) in each of the second processing units (SPCs).

When a current first processing unit (GOS) is a closed GOS, for example,three-dimensional data encoding device 100 encodes a current secondprocessing unit (SPC) included in such current first processing unit(GOS) by referring to another second processing unit (SPC) included inthe current first processing unit (GOS). Stated differently,three-dimensional data encoding device 100 refers to no secondprocessing unit (SPC) included in a first processing unit (GOS) that isdifferent from the current first processing unit (GOS).

Meanwhile, when a current first processing unit (GOS) is an open GOS,three-dimensional data encoding device 100 encodes a current secondprocessing unit (SPC) included in such current first processing unit(GOS) by referring to another second processing unit (SPC) included inthe current first processing unit (GOS) or a second processing unit(SPC) included in a first processing unit (GOS) that is different fromthe current first processing unit (GOS).

Also, three-dimensional data encoding device 100 selects, as the type ofa current second processing unit (SPC), one of the following: a firsttype (I-SPC) in which another second processing unit (SPC) is notreferred to; a second type (P-SPC) in which another single secondprocessing unit (SPC) is referred to; and a third type in which othertwo second processing units (SPC) are referred to. Three-dimensionaldata encoding device 100 encodes the current second processing unit(SPC) in accordance with the selected type.

Next, the structure and the operation flow of the three-dimensional datadecoding device according to the present embodiment will be described.FIG. 8 is a block diagram of three-dimensional data decoding device 200according to the present embodiment. FIG. 9 is a flowchart of an exampleoperation performed by three-dimensional data decoding device 200.

Three-dimensional data decoding device 200 shown in FIG. 8 decodesencoded three-dimensional data 211, thereby generating decodedthree-dimensional data 212. Encoded three-dimensional data 211 here is,for example, encoded three-dimensional data 112 generated bythree-dimensional data encoding device 100. Such three-dimensional datadecoding device 200 includes obtainer 201, decoding start GOS determiner202, decoding SPC determiner 203, and decoder 204.

First, obtainer 201 obtains encoded three-dimensional data 211 (S201).Next, decoding start GOS determiner 202 determines a current GOS fordecoding (S202). More specifically, decoding start GOS determiner 202refers to meta-information stored in encoded three-dimensional data 211or stored separately from the encoded three-dimensional data todetermine, as the current GOS, a GOS that includes a SPC correspondingto the spatial position, the object, or the time from which decoding isto start.

Next, decoding SPC determiner 203 determines the type(s) (I, P, and/orB) of SPCs to be decoded in the GOS (S203). For example, decoding SPCdeterminer 203 determines whether to (1) decode only I-SPC(s), (2) todecode I-SPC(s) and P-SPCs, or (3) to decode SPCs of all types. Notethat the present step may not be performed, when the type(s) of SPCs tobe decoded are previously determined such as when all SPCs arepreviously determined to be decoded.

Next, decoder 204 obtains an address location within encodedthree-dimensional data 211 from which a SPC that comes first in the GOSin the decoding order (the same as the encoding order) starts. Decoder204 obtains the encoded data of the first SPC from the address location,and sequentially decodes the SPCs from such first SPC (S204). Note thatthe address location is stored in the meta-information, etc.

Three-dimensional data decoding device 200 decodes decodedthree-dimensional data 212 as thus described. More specifically,three-dimensional data decoding device 200 decodes each encodedthree-dimensional data 211 of the first processing units (GOSs), eachbeing a random access unit and being associated with three-dimensionalcoordinates, thereby generating decoded three-dimensional data 212 ofthe first processing units (GOSs). Even more specifically,three-dimensional data decoding device 200 decodes each of the secondprocessing units (SPCs) in each of the first processing units (GOSs).Three-dimensional data decoding device 200 further decodes each of thethird processing units (VLMs) in each of the second processing units(SPCs).

The following describes meta-information for random access. Suchmeta-information is generated by three-dimensional data encoding device100, and included in encoded three-dimensional data 112 (211).

In the conventional random access for a two-dimensional moving picture,decoding starts from the first frame in a random access unit that isclose to a specified time. Meanwhile, in addition to times, randomaccess to spaces (coordinates, objects, etc.) is assumed to be performedin a world.

To enable random access to at least three elements of coordinates,objects, and times, tables are prepared that associate the respectiveelements with the GOS index numbers. Furthermore, the GOS index numbersare associated with the addresses of the respective first I-SPCs in theGOSs. FIG. 10 is a diagram showing example tables included in themeta-information. Note that not all the tables shown in FIG. 10 arerequired to be used, and thus at least one of the tables is used.

The following describes an example in which random access is performedfrom coordinates as a starting point. To access the coordinates (x2, y2,and z2), the coordinates-GOS table is first referred to, which indicatesthat the point corresponding to the coordinates (x2, y2, and z2) isincluded in the second GOS. Next, the GOS-address table is referred to,which indicates that the address of the first I-SPC in the second GOS isaddr(2). As such, decoder 204 obtains data from this address to startdecoding.

Note that the addresses may either be logical addresses or physicaladdresses of an HDD or a memory. Alternatively, information thatidentifies file segments may be used instead of addresses. File segmentsare, for example, units obtained by segmenting at least one GOS, etc.

When an object spans across a plurality of GOSs, the object-GOS tablemay show a plurality of GOSs to which such object belongs. When suchplurality of GOSs are closed GOSs, the encoding device and the decodingdevice can perform encoding or decoding in parallel. Meanwhile, whensuch plurality of GOSs are open GOSs, a higher compression efficiency isachieved by the plurality of GOSs referring to each other.

Example objects include a person, an animal, a car, a bicycle, a signal,and a building serving as a landmark. For example, three-dimensionaldata encoding device 100 extracts keypoints specific to an object from athree-dimensional point cloud, etc., when encoding a world, and detectsthe object on the basis of such keypoints to set the detected object asa random access point.

As thus described, three-dimensional data encoding device 100 generatesfirst information indicating a plurality of first processing units(GOSs) and the three-dimensional coordinates associated with therespective first processing units (GOSs). Encoded three-dimensional data112 (211) includes such first information. The first information furtherindicates at least one of objects, times, and data storage locationsthat are associated with the respective first processing units (GOSs).

Three-dimensional data decoding device 200 obtains the first informationfrom encoded three-dimensional data 211. Using such first information,three-dimensional data decoding device 200 identifies encodedthree-dimensional data 211 of the first processing unit that correspondsto the specified three-dimensional coordinates, object, or time, anddecodes encoded three-dimensional data 211.

The following describes an example of other meta-information. Inaddition to the meta-information for random access, three-dimensionaldata encoding device 100 may also generate and store meta-information asdescribed below, and three-dimensional data decoding device 200 may usesuch meta-information at the time of decoding.

When three-dimensional data is used as map information, for example, aprofile is defined in accordance with the intended use, and informationindicating such profile may be included in meta-information. Forexample, a profile is defined for an urban or a suburban area, or for aflying object, and the maximum or minimum size, etc. of a world, a SPCor a VLM, etc. is defined in each profile. For example, more detailedinformation is required for an urban area than for a suburban area, andthus the minimum VLM size is set to small. The meta-information mayinclude tag values indicating object types.

Each of such tag values is associated with VLMs, SPCs, or GOSs thatconstitute an object. For example, a tag value may be set for eachobject type in a manner, for example, that the tag value “0” indicates“person,” the tag value “1” indicates “car,” and the tag value “2”indicates “signal.” Alternatively, when an object type is hard to judge,or such judgment is not required, a tag value may be used that indicatesthe size or the attribute indicating, for example, whether an object isa dynamic object or a static object.

The meta-information may also include information indicating a range ofthe spatial region occupied by a world.

The meta-information may also store the SPC or V×L size as headerinformation common to the whole stream of the encoded data or to aplurality of SPCs, such as SPCs in a GOS.

The meta-information may also include identification information on adistance sensor or a camera that has been used to generate a pointcloud, or information indicating the positional accuracy of a pointgroup in the point cloud.

The meta-information may also include information indicating whether aworld is made only of static objects or includes a dynamic object.

The following describes variations of the present embodiment.

The encoding device or the decoding device may encode or decode two ormore mutually different SPCs or GOSs in parallel. GOSs to be encoded ordecoded in parallel can be determined on the basis of meta-information,etc. indicating the spatial positions of the GOSs.

When three-dimensional data is used as a spatial map for use by a car ora flying object, etc. in traveling, or for creation of such a spatialmap, for example, the encoding device or the decoding device may encodeor decode GOSs or SPCs included in a space that is identified on thebasis of GPS information, the route information, the zoom magnification,etc.

The decoding device may also start decoding sequentially from a spacethat is close to the self-location or the traveling route. The encodingdevice or the decoding device may give a lower priority to a spacedistant from the self-location or the traveling route than the priorityof a nearby space to encode or decode such distant place. To “give alower priority” means here, for example, to lower the priority in theprocessing sequence, to decrease the resolution (to apply decimation inthe processing), or to lower the image quality (to increase the encodingefficiency by, for example, setting the quantization step to larger).

When decoding encoded data that is hierarchically encoded in a space,the decoding device may decode only the bottom level in the hierarchy.

The decoding device may also start decoding preferentially from thebottom level of the hierarchy in accordance with the zoom magnificationor the intended use of the map.

For self-location estimation or object recognition, etc. involved in theself-driving of a car or a robot, the encoding device or the decodingdevice may encode or decode regions at a lower resolution, except for aregion that is lower than or at a specified height from the ground (theregion to be recognized).

The encoding device may also encode point clouds representing thespatial shapes of a room interior and a room exterior separately. Forexample, the separation of a GOS representing a room interior (interiorGOS) and a GOS representing a room exterior (exterior GOS) enables thedecoding device to select a GOS to be decoded in accordance with aviewpoint location, when using the encoded data.

The encoding device may also encode an interior GOS and an exterior GOShaving close coordinates so that such GOSs come adjacent to each otherin an encoded stream. For example, the encoding device associates theidentifiers of such GOSs with each other, and stores informationindicating the associated identifiers into the meta-information that isstored in the encoded stream or stored separately. This enables thedecoding device to refer to the information in the meta-information toidentify an interior GOS and an exterior GOS having close coordinates

The encoding device may also change the GOS size or the SPC sizedepending on whether a GOS is an interior GOS or an exterior GOS. Forexample, the encoding device sets the size of an interior GOS to smallerthan the size of an exterior GOS. The encoding device may also changethe accuracy of extracting keypoints from a point cloud, or the accuracyof detecting objects, for example, depending on whether a GOS is aninterior GOS or an exterior GOS.

The encoding device may also add, to encoded data, information by whichthe decoding device displays objects with a distinction between adynamic object and a static object. This enables the decoding device todisplay a dynamic object together with, for example, a red box orletters for explanation. Note that the decoding device may display onlya red box or letters for explanation, instead of a dynamic object. Thedecoding device may also display more particular object types. Forexample, a red box may be used for a car, and a yellow box may be usedfor a person.

The encoding device or the decoding device may also determine whether toencode or decode a dynamic object and a static object as a different SPCor GOS, in accordance with, for example, the appearance frequency ofdynamic objects or a ratio between static objects and dynamic objects.For example, when the appearance frequency or the ratio of dynamicobjects exceeds a threshold, a SPC or a GOS including a mixture of adynamic object and a static object is accepted, while when theappearance frequency or the ratio of dynamic objects is below athreshold, a SPC or GOS including a mixture of a dynamic object and astatic object is unaccepted.

When detecting a dynamic object not from a point cloud but fromtwo-dimensional image information of a camera, the encoding device mayseparately obtain information for identifying a detection result (box orletters) and the object position, and encode these items of informationas part of the encoded three-dimensional data. In such a case, thedecoding device superimposes auxiliary information (box or letters)indicating the dynamic object onto a resultant of decoding a staticobject to display it.

The encoding device may also change the sparseness and denseness of VXLsor VLMs in a SPC in accordance with the degree of complexity of theshape of a static object. For example, the encoding device sets VXLs orVLMs at a higher density as the shape of a static object is morecomplex. The encoding device may further determine a quantization step,etc. for quantizing spatial positions or color information in accordancewith the sparseness and denseness of VXLs or VLMs. For example, theencoding device sets the quantization step to smaller as the density ofVXLs or VLMs is higher.

As described above, the encoding device or the decoding device accordingto the present embodiment encodes or decodes a space on a SPC-by-SPCbasis that includes coordinate information.

Furthermore, the encoding device and the decoding device performencoding or decoding on a volume-by-volume basis in a SPC. Each volumeincludes a voxel, which is the minimum unit in which positioninformation is associated.

Also, using a table that associates the respective elements of spatialinformation including coordinates, objects, and times with GOSs or usinga table that associates these elements with each other, the encodingdevice and the decoding device associate any ones of the elements witheach other to perform encoding or decoding. The decoding device uses thevalues of the selected elements to determine the coordinates, andidentifies a volume, a voxel, or a SPC from such coordinates to decode aSPC including such volume or voxel, or the identified SPC.

Furthermore, the encoding device determines a volume, a voxel, or a SPCthat is selectable in accordance with the elements, through extractionof keypoints and object recognition, and encodes the determined volume,voxel, or SPC, as a volume, a voxel, or a SPC to which random access ispossible.

SPCs are classified into three types: I-SPC that is singly encodable ordecodable; P-SPC that is encoded or decoded by referring to any one ofthe processed SPCs; and B-SPC that is encoded or decoded by referring toany two of the processed SPCs.

At least one volume corresponds to a static object or a dynamic object.A SPC including a static object and a SPC including a dynamic object areencoded or decoded as mutually different GOSs. Stated differently, a SPCincluding a static object and a SPC including a dynamic object areassigned to different GOSs.

Dynamic objects are encoded or decoded on an object-by-object basis, andare associated with at least one SPC including a static object. Stateddifferently, a plurality of dynamic objects are individually encoded,and the obtained encoded data of the dynamic objects is associated witha SPC including a static object.

The encoding device and the decoding device give an increased priorityto I-SPC(s) in a GOS to perform encoding or decoding. For example, theencoding device performs encoding in a manner that prevents thedegradation of I-SPCs (in a manner that enables the originalthree-dimensional data to be reproduced with a higher fidelity afterdecoded). The decoding device decodes, for example, only I-SPCs.

The encoding device may change the frequency of using I-SPCs dependingon the sparseness and denseness or the number (amount) of the objects ina world to perform encoding. Stated differently, the encoding devicechanges the frequency of selecting I-SPCs depending on the number or thesparseness and denseness of the objects included in thethree-dimensional data. For example, the encoding device uses I-SPCs ata higher frequency as the density of the objects in a world is higher.

The encoding device also sets random access points on a GOS-by-GOSbasis, and stores information indicating the spatial regionscorresponding to the GOSs into the header information.

The encoding devices uses, for example, a default value as the spatialsize of a GOS. Note that the encoding device may change the GOS sizedepending on the number (amount) or the sparseness and denseness ofobjects or dynamic objects. For example, the encoding device sets thespatial size of a GOS to smaller as the density of objects or dynamicobjects is higher or the number of objects or dynamic objects isgreater.

Also, each SPC or volume includes a keypoint group that is derived byuse of information obtained by a sensor such as a depth sensor, agyroscope sensor, or a camera sensor. The coordinates of the keypointsare set at the central positions of the respective voxels. Furthermore,finer voxels enable highly accurate position information.

The keypoint group is derived by use of a plurality of pictures. Aplurality of pictures include at least two types of time information:the actual time information and the same time information common to aplurality of pictures that are associated with SPCs (for example, theencoding time used for rate control, etc.).

Also, encoding or decoding is performed on a GOS-by-GOS basis thatincludes at least one SPC.

The encoding device and the decoding device predict P-SPCs or B-SPCs ina current GOS by referring to SPCs in a processed GOS.

Alternatively, the encoding device and the decoding device predictP-SPCs or B-SPCs in a current GOS, using the processed SPCs in thecurrent GOS, without referring to a different GOS.

Furthermore, the encoding device and the decoding device transmit orreceive an encoded stream on a world-by-world basis that includes atleast one GOS.

Also, a GOS has a layer structure in one direction at least in a world,and the encoding device and the decoding device start encoding ordecoding from the bottom layer. For example, a random accessible GOSbelongs to the lowermost layer. A GOS that belongs to the same layer ora lower layer is referred to in a GOS that belongs to an upper layer.Stated differently, a GOS is spatially divided in a predetermineddirection in advance to have a plurality of layers, each including atleast one SPC. The encoding device and the decoding device encode ordecode each SPC by referring to a SPC included in the same layer as theeach SPC or a SPC included in a layer lower than that of the each SPC.

Also, the encoding device and the decoding device successively encode ordecode GOSs on a world-by-world basis that includes such GOSs. In sodoing, the encoding device and the decoding device write or read outinformation indicating the order (direction) of encoding or decoding asmetadata. Stated differently, the encoded data includes informationindicating the order of encoding a plurality of GOSs.

The encoding device and the decoding device also encode or decodemutually different two or more SPCs or GOSs in parallel.

Furthermore, the encoding device and the decoding device encode ordecode the spatial information (coordinates, size, etc.) on a SPC or aGOS.

The encoding device and the decoding device encode or decode SPCs orGOSs included in an identified space that is identified on the basis ofexternal information on the self-location or/and region size, such asGPS information, route information, or magnification.

The encoding device or the decoding device gives a lower priority to aspace distant from the self-location than the priority of a nearby spaceto perform encoding or decoding.

The encoding device sets a direction at one of the directions in aworld, in accordance with the magnification or the intended use, toencode a GOS having a layer structure in such direction. Also, thedecoding device decodes a GOS having a layer structure in one of thedirections in a world that has been set in accordance with themagnification or the intended use, preferentially from the bottom layer.

The encoding device changes the accuracy of extracting keypoints, theaccuracy of recognizing objects, or the size of spatial regions, etc.included in a SPC, depending on whether an object is an interior objector an exterior object. Note that the encoding device and the decodingdevice encode or decode an interior GOS and an exterior GOS having closecoordinates in a manner that these GOSs come adjacent to each other in aworld, and associates their identifiers with each other for encoding anddecoding.

Embodiment 2

When using encoded data of a point cloud in an actual device or service,it is desirable that necessary information be transmitted/received inaccordance with the intended use to reduce the network bandwidth.However, there has been no such functionality in the structure ofencoding three-dimensional data, nor an encoding method therefor.

The present embodiment describes a three-dimensional data encodingmethod and a three-dimensional data encoding device for providing thefunctionality of transmitting/receiving only necessary information inencoded data of a three-dimensional point cloud in accordance with theintended use, as well as a three-dimensional data decoding method and athree-dimensional data decoding device for decoding such encoded data.

A voxel (VXL) with a feature greater than or equal to a given amount isdefined as a feature voxel (FVXL), and a world (WLD) constituted byFVXLs is defined as a sparse world (SWLD). FIG. 11 is a diagram showingexample structures of a sparse world and a world. A SWLD includes:FGOSs, each being a GOS constituted by FVXLs; FSPCs, each being a SPCconstituted by FVXLs; and FVLMs, each being a VLM constituted by FVXLs.The data structure and prediction structure of a FGOS, a FSPC, and aFVLM may be the same as those of a GOS, a SPC, and a VLM.

A feature represents the three-dimensional position information on a VXLor the visible-light information on the position of a VXL. A largenumber of features are detected especially at a corner, an edge, etc. ofa three-dimensional object. More specifically, such a feature is athree-dimensional feature or a visible-light feature as described below,but may be any feature that represents the position, luminance, or colorinformation, etc. on a VXL.

Used as three-dimensional features are signature of histograms oforientations (SHOT) features, point feature histograms (PFH) features,or point pair feature (PPF) features.

SHOT features are obtained by dividing the periphery of a VXL, andcalculating an inner product of the reference point and the normalvector of each divided region to represent the calculation result as ahistogram. SHOT features are characterized by a large number ofdimensions and high-level feature representation.

PFH features are obtained by selecting a large number of two point pairsin the vicinity of a VXL, and calculating the normal vector, etc. fromeach two point pair to represent the calculation result as a histogram.PFH features are histogram features, and thus are characterized byrobustness against a certain extent of disturbance and also high-levelfeature representation.

PPF features are obtained by using a normal vector, etc. for each twopoints of VXLs. PPF features, for which all VXLs are used, hasrobustness against occlusion.

Used as visible-light features are scale-invariant feature transform(SIFT), speeded up robust features (SURF), or histogram of orientedgradients (HOG), etc. that use information on an image such as luminancegradient information.

A SWLD is generated by calculating the above-described features of therespective VXLs in a WLD to extract FVXLs. Here, the SWLD may be updatedevery time the WLD is updated, or may be regularly updated after theelapse of a certain period of time, regardless of the timing at whichthe WLD is up dated.

A SWLD may be generated for each type of features. For example,different SWLDs may be generated for the respective types of features,such as SWLD1 based on SHOT features and SWLD2 based on SIFT features sothat SWLDs are selectively used in accordance with the intended use.Also, the calculated feature of each FVXL may be held in each FVXL asfeature information.

Next, the usage of a sparse world (SWLD) will be described. A SWLDincludes only feature voxels (FVXLs), and thus its data size is smallerin general than that of a WLD that includes all VXLs.

In an application that utilizes features for a certain purpose, the useof information on a SWLD instead of a WLD reduces the time required toread data from a hard disk, as well as the bandwidth and the timerequired for data transfer over a network. For example, a WLD and a SWLDare held in a server as map information so that map information to besent is selected between the WLD and the SWLD in accordance with arequest from a client. This reduces the network bandwidth and the timerequired for data transfer. More specific examples will be describedbelow.

FIG. 12 and FIG. 13 are diagrams showing usage examples of a SWLD and aWLD. As FIG. 12 shows, when client 1, which is a vehicle-mounted device,requires map information to use it for self-location determination,client 1 sends to a server a request for obtaining map data forself-location estimation (S301). The server sends to client 1 the SWLDin response to the obtainment request (S302). Client 1 uses the receivedSWLD to determine the self-location (S303). In so doing, client 1obtains VXL information on the periphery of client 1 through variousmeans including a distance sensor such as a rangefinder, as well as astereo camera and a combination of a plurality of monocular cameras.Client 1 then estimates the self-location information from the obtainedVXL information and the SWLD. Here, the self-location informationincludes three-dimensional position information, orientation, etc. ofclient 1.

As FIG. 13 shows, when client 2, which is a vehicle-mounted device,requires map information to use it for rendering a map such as athree-dimensional map, client 2 sends to the server a request forobtaining map data for map rendering (S311). The server sends to client2 the WLD in response to the obtainment request (S312). Client 2 usesthe received WLD to render a map (S313). In so doing, client 2 uses, forexample, an image client 2 has captured by a visible-light camera, etc.and the WLD obtained from the server to create a rendering image, andrenders such created image onto a screen of a car navigation system,etc.

As described above, the server sends to a client a SWLD when thefeatures of the respective VXLs are mainly required such as in the caseof self-location estimation, and sends to a client a WLD when detailedVXL information is required such as in the case of map rendering. Thisallows for an efficient sending/receiving of map data.

Note that a client may self-judge which one of a SWLD and a WLD isnecessary, and request the server to send a SWLD or a WLD. Also, theserver may judge which one of a SWLD and a WLD to send in accordancewith the status of the client or a network.

Next, a method will be described of switching the sending/receivingbetween a sparse world (SWLD) and a world (WLD).

Whether to receive a WLD or a SWLD may be switched in accordance withthe network bandwidth. FIG. 14 is a diagram showing an example operationin such case. For example, when a low-speed network is used that limitsthe usable network bandwidth, such as in a long term evolution (LTE)environment, a client accesses the server over a low-speed network(S321), and obtains the SWLD from the server as map information (S322).Meanwhile, when a high-speed network is used that has an adequatelybroad network bandwidth, such as in a WiFi environment, a clientaccesses the server over a high-speed network (S323), and obtains theWLD from the server (S324). This enables the client to obtainappropriate map information in accordance with the network bandwidthsuch client is using.

More specifically, a client receives the SWLD over a LTE network when inoutdoors, and obtains the WLD over a WiFi network when in indoors suchas in a facility. This enables the client to obtain more detailed mapinformation on indoor environment.

As described above, a client may request for a WLD or a SWLD inaccordance with the bandwidth of a network such client is using.Alternatively, the client may send to the server information indicatingthe bandwidth of a network such client is using, and the server may sendto the client data (the WLD or the SWLD) suitable for such client inaccordance with the information. Alternatively, the server may identifythe network bandwidth the client is using, and send to the client data(the WLD or the SWLD) suitable for such client.

Also, whether to receive a WLD or a SWLD may be switched in accordancewith the speed of traveling. FIG. 15 is a diagram showing an exampleoperation in such case. For example, when traveling at a high speed(S331), a client receives the SWLD from the server (S332). Meanwhile,when traveling at a low speed (S333), the client receives the WLD fromthe server (S334). This enables the client to obtain map informationsuitable to the speed, while reducing the network bandwidth. Morespecifically, when traveling on an expressway, the client receives theSWLD with a small data amount, which enables the update of rough mapinformation at an appropriate speed. Meanwhile, when traveling on ageneral road, the client receives the WLD, which enables the obtainmentof more detailed map information.

As described above, the client may request the server for a WLD or aSWLD in accordance with the traveling speed of such client.Alternatively, the client may send to the server information indicatingthe traveling speed of such client, and the server may send to theclient data (the WLD or the SWLD) suitable to such client in accordancewith the information. Alternatively, the server may identify thetraveling speed of the client to send data (the WLD or the SWLD)suitable to such client.

Also, the client may obtain, from the server, a SWLD first, from whichthe client may obtain a WLD of an important region. For example, whenobtaining map information, the client first obtains a SWLD for rough mapinformation, from which the client narrows to a region in which featuressuch as buildings, signals, or persons appear at high frequency so thatthe client can later obtain a WLD of such narrowed region. This enablesthe client to obtain detailed information on a necessary region, whilereducing the amount of data received from the server.

The server may also create from a WLD different SWLDs for the respectiveobjects, and the client may receive SWLDs in accordance with theintended use. This reduces the network bandwidth. For example, theserver recognizes persons or cars in a WLD in advance, and creates aSWLD of persons and a SWLD of cars. The client, when wishing to obtaininformation on persons around the client, receives the SWLD of persons,and when wising to obtain information on cars, receives the SWLD ofcars. Such types of SWLDs may be distinguished by information (flag, ortype, etc.) added to the header, etc.

Next, the structure and the operation flow of the three-dimensional dataencoding device (e.g., a server) according to the present embodimentwill be described. FIG. 16 is a block diagram of three-dimensional dataencoding device 400 according to the present embodiment. FIG. 17 is aflowchart of three-dimensional data encoding processes performed bythree-dimensional data encoding device 400.

Three-dimensional data encoding device 400 shown in FIG. 16 encodesinput three-dimensional data 411, thereby generating encodedthree-dimensional data 413 and encoded three-dimensional data 414, eachbeing an encoded stream. Here, encoded three-dimensional data 413 isencoded three-dimensional data corresponding to a WLD, and encodedthree-dimensional data 414 is encoded three-dimensional datacorresponding to a SWLD. Such three-dimensional data encoding device 400includes, obtainer 401, encoding region determiner 402, SWLD extractor403, WLD encoder 404, and SWLD encoder 405.

First, as FIG. 17 shows, obtainer 401 obtains input three-dimensionaldata 411, which is point group data in a three-dimensional space (S401).

Next, encoding region determiner 402 determines a current spatial regionfor encoding on the basis of a spatial region in which the point clouddata is present (S402).

Next, SWLD extractor 403 defines the current spatial region as a WLD,and calculates the feature from each VXL included in the WLD. Then, SWLDextractor 403 extracts VXLs having an amount of features greater than orequal to a predetermined threshold, defines the extracted VXLs as FVXLs,and adds such FVXLs to a SWLD, thereby generating extractedthree-dimensional data 412 (S403). Stated differently, extractedthree-dimensional data 412 having an amount of features greater than orequal to the threshold is extracted from input three-dimensional data411.

Next, WLD encoder 404 encodes input three-dimensional data 411corresponding to the WLD, thereby generating encoded three-dimensionaldata 413 corresponding to the WLD (S404). In so doing, WLD encoder 404adds to the header of encoded three-dimensional data 413 informationthat distinguishes that such encoded three-dimensional data 413 is astream including a WLD.

SWLD encoder 405 encodes extracted three-dimensional data 412corresponding to the SWLD, thereby generating encoded three-dimensionaldata 414 corresponding to the SWLD (S405). In so doing, SWLD encoder 405adds to the header of encoded three-dimensional data 414 informationthat distinguishes that such encoded three-dimensional data 414 is astream including a SWLD.

Note that the process of generating encoded three-dimensional data 413and the process of generating encoded three-dimensional data 414 may beperformed in the reverse order. Also note that a part or all of theseprocesses may be performed in parallel.

A parameter “world_type” is defined, for example, as information addedto each header of encoded three-dimensional data 413 and encodedthree-dimensional data 414. world_type=0 indicates that a streamincludes a WLD, and world_type=1 indicates that a stream includes aSWLD. An increased number of values may be further assigned to define alarger number of types, e.g., world_type=2. Also, one of encodedthree-dimensional data 413 and encoded three-dimensional data 414 mayinclude a specified flag. For example, encoded three-dimensional data414 may be assigned with a flag indicating that such stream includes aSWLD. In such a case, the decoding device can distinguish whether suchstream is a stream including a WLD or a stream including a SWLD inaccordance with the presence/absence of the flag.

Also, an encoding method used by WLD encoder 404 to encode a WLD may bedifferent from an encoding method used by SWLD encoder 405 to encode aSWLD.

For example, data of a SWLD is decimated, and thus can have a lowercorrelation with the neighboring data than that of a WLD. For thisreason, of intra prediction and inter prediction, inter prediction maybe more preferentially performed in an encoding method used for a SWLDthan in an encoding method used for a WLD.

Also, an encoding method used for a SWLD and an encoding method used fora WLD may represent three-dimensional positions differently. Forexample, three-dimensional coordinates may be used to represent thethree-dimensional positions of FVXLs in a SWLD and an octree describedbelow may be used to represent three-dimensional positions in a WLD, andvice versa.

Also, SWLD encoder 405 performs encoding in a manner that encodedthree-dimensional data 414 of a SWLD has a smaller data size than thedata size of encoded three-dimensional data 413 of a WLD. A SWLD canhave a lower inter-data correlation, for example, than that of a WLD asdescribed above. This can lead to a decreased encoding efficiency, andthus to encoded three-dimensional data 414 having a larger data sizethan the data size of encoded three-dimensional data 413 of a WLD. Whenthe data size of the resulting encoded three-dimensional data 414 islarger than the data size of encoded three-dimensional data 413 of aWLD, SWLD encoder 405 performs encoding again to re-generate encodedthree-dimensional data 414 having a reduced data size.

For example, SWLD extractor 403 re-generates extracted three-dimensionaldata 412 having a reduced number of keypoints to be extracted, and SWLDencoder 405 encodes such extracted three-dimensional data 412.Alternatively, SWLD encoder 405 may perform more coarse quantization.More coarse quantization is achieved, for example, by rounding the datain the lowermost level in an octree structure described below.

When failing to decrease the data size of encoded three-dimensional data414 of the SWLD to smaller than the data size of encodedthree-dimensional data 413 of the WLD, SWLD encoder 405 may not generateencoded three-dimensional data 414 of the SWLD. Alternatively, encodedthree-dimensional data 413 of the WLD may be copied as encodedthree-dimensional data 414 of the SWLD. Stated differently, encodedthree-dimensional data 413 of the WLD may be used as it is as encodedthree-dimensional data 414 of the SWLD.

Next, the structure and the operation flow of the three-dimensional datadecoding device (e.g., a client) according to the present embodimentwill be described. FIG. 18 is a block diagram of three-dimensional datadecoding device 500 according to the present embodiment. FIG. 19 is aflowchart of three-dimensional data decoding processes performed bythree-dimensional data decoding device 500.

Three-dimensional data decoding device 500 shown in FIG. 18 decodesencoded three-dimensional data 511, thereby generating decodedthree-dimensional data 512 or decoded three-dimensional data 513.Encoded three-dimensional data 511 here is, for example, encodedthree-dimensional data 413 or encoded three-dimensional data 414generated by three-dimensional data encoding device 400.

Such three-dimensional data decoding device 500 includes obtainer 501,header analyzer 502, WLD decoder 503, and SWLD decoder 504.

First, as FIG. 19 shows, obtainer 501 obtains encoded three-dimensionaldata 511 (S501). Next, header analyzer 502 analyzes the header ofencoded three-dimensional data 511 to identify whether encodedthree-dimensional data 511 is a stream including a WLD or a streamincluding a SWLD (S502). For example, the above-described parameterworld_type is referred to in making such identification.

When encoded three-dimensional data 511 is a stream including a WLD (Yesin S503), WLD decoder 503 decodes encoded three-dimensional data 511,thereby generating decoded three-dimensional data 512 of the WLD (S504).Meanwhile, when encoded three-dimensional data 511 is a stream includinga SWLD (No in S503), SWLD decoder 504 decodes encoded three-dimensionaldata 511, thereby generating decoded three-dimensional data 513 of theSWLD (S505).

Also, as in the case of the encoding device, a decoding method used byWLD decoder 503 to decode a WLD may be different from a decoding methodused by SWLD decoder 504 to decode a SWLD. For example, of intraprediction and inter prediction, inter prediction may be morepreferentially performed in a decoding method used for a SWLD than in adecoding method used for a WLD.

Also, a decoding method used for a SWLD and a decoding method used for aWLD may represent three-dimensional positions differently. For example,three-dimensional coordinates may be used to represent thethree-dimensional positions of FVXLs in a SWLD and an octree describedbelow may be used to represent three-dimensional positions in a WLD, andvice versa.

Next, an octree representation will be described, which is a method ofrepresenting three-dimensional positions. VXL data included inthree-dimensional data is converted into an octree structure beforeencoded. FIG. 20 is a diagram showing example VXLs in a WLD. FIG. 21 isa diagram showing an octree structure of the WLD shown in FIG. 20. Anexample shown in FIG. 20 illustrates three VXLs 1 to 3 that includepoint groups (hereinafter referred to as effective VXLs). As FIG. 21shows, the octree structure is made of nodes and leaves. Each node has amaximum of eight nodes or leaves. Each leaf has VXL information. Here,of the leaves shown in FIG. 21, leaf 1, leaf 2, and leaf 3 representVXL1, VXL2, and VXL3 shown in FIG. 20, respectively.

More specifically, each node and each leaf corresponds to athree-dimensional position. Node 1 corresponds to the entire block shownin FIG. 20. The block that corresponds to node 1 is divided into eightblocks. Of these eight blocks, blocks including effective VXLs are setas nodes, while the other blocks are set as leaves. Each block thatcorresponds to a node is further divided into eight nodes or leaves.These processes are repeated by the number of times that is equal to thenumber of levels in the octree structure. All blocks in the lowermostlevel are set as leaves.

FIG. 22 is a diagram showing an example SWLD generated from the WLDshown in FIG. 20. VXL1 and VXL2 shown in FIG. 20 are judged as FVXL1 andFVXL2 as a result of feature extraction, and thus are added to the SWLD.Meanwhile, VXL3 is not judged as a FVXL, and thus is not added to theSWLD. FIG. 23 is a diagram showing an octree structure of the SWLD shownin FIG. 22. In the octree structure shown in FIG. 23, leaf 3corresponding to VXL3 shown in FIG. 21 is deleted. Consequently, node 3shown in FIG. 21 has lost an effective VXL, and has changed to a leaf.As described above, a SWLD has a smaller number of leaves in generalthan a WLD does, and thus the encoded three-dimensional data of the SWLDis smaller than the encoded three-dimensional data of the WLD.

The following describes variations of the present embodiment.

For self-location estimation, for example, a client, being avehicle-mounted device, etc., may receive a SWLD from the server to usesuch SWLD to estimate the self-location. Meanwhile, for obstacledetection, the client may detect obstacles by use of three-dimensionalinformation on the periphery obtained by such client through variousmeans including a distance sensor such as a rangefinder, as well as astereo camera and a combination of a plurality of monocular cameras.

In general, a SWLD is less likely to include VXL data on a flat region.As such, the server may hold a subsample world (subWLD) obtained bysubsampling a WLD for detection of static obstacles, and send to theclient the SWLD and the subWLD. This enables the client to performself-location estimation and obstacle detection on the client's part,while reducing the network bandwidth.

When the client renders three-dimensional map data at a high speed, mapinformation having a mesh structure is more useful in some cases. Assuch, the server may generate a mesh from a WLD to hold it beforehand asa mesh world (MWLD). For example, when wishing to perform coarsethree-dimensional rendering, the client receives a MWLD, and whenwishing to perform detailed three-dimensional rendering, the clientreceives a WLD. This reduces the network bandwidth.

In the above description, the server sets, as FVXLs, VXLs having anamount of features greater than or equal to the threshold, but theserver may calculate FVXLs by a different method. For example, theserver may judge that a VXL, a VLM, a SPC, or a GOS that constitutes asignal, or an intersection, etc. as necessary for self-locationestimation, driving assist, or self-driving, etc., and incorporate suchVXL, VLM, SPC, or GOS into a SWLD as a FVXL, a FVLM, a FSPC, or a FGOS.Such judgment may be made manually. Also, FVXLs, etc. that have been seton the basis of an amount of features may be added to FVXLs, etc.obtained by the above method. Stated differently, SWLD extractor 403 mayfurther extract, from input three-dimensional data 411, datacorresponding to an object having a predetermined attribute as extractedthree-dimensional data 412.

Also, that a VXL, a VLM, a SPC, or a GOS are necessary for such intendedusage may labelled separately from the features. The server mayseparately hold, as an upper layer of a SWLD (e.g., a lane world), FVXLsof a signal or an intersection, etc. necessary for self-locationestimation, driving assist, or self-driving, etc.

The server may also add an attribute to VXLs in a WLD on a random accessbasis or on a predetermined unit basis. An attribute, for example,includes information indicating whether VXLs are necessary forself-location estimation, or information indicating whether VXLs areimportant as traffic information such as a signal, or an intersection,etc. An attribute may also include a correspondence between VXLs andfeatures (intersection, or road, etc.) in lane information (geographicdata files (GDF), etc.).

A method as described below may be used to update a WLD or a SWLD.

Update information indicating changes, etc. in a person, a roadwork, ora tree line (for trucks) is uploaded to the server as point groups ormeta data. The server updates a WLD on the basis of such uploadedinformation, and then updates a SWLD by use of the updated WLD.

The client, when detecting a mismatch between the three-dimensionalinformation such client has generated at the time of self-locationestimation and the three-dimensional information received from theserver, may send to the server the three-dimensional information suchclient has generated, together with an update notification. In such acase, the server updates the SWLD by use of the WLD. When the SWLD isnot to be updated, the server judges that the WLD itself is old.

In the above description, information that distinguishes whether anencoded stream is that of a WLD or a SWLD is added as header informationof the encoded stream. However, when there are many types of worlds suchas a mesh world and a lane world, information that distinguishes thesetypes of the worlds may be added to header information. Also, when thereare many SWLDs with different amounts of features, information thatdistinguishes the respective SWLDs may be added to header information.

In the above description, a SWLD is constituted by FVXLs, but a SWLD mayinclude VXLs that have not been judged as FVXLs. For example, a SWLD mayinclude an adjacent VXL used to calculate the feature of a FVXL. Thisenables the client to calculate the feature of a FVXL when receiving aSWLD, even in the case where feature information is not added to eachFVXL of the SWLD. In such a case, the SWLD may include information thatdistinguishes whether each VXL is a FVXL or a VXL.

As described above, three-dimensional data encoding device 400 extracts,from input three-dimensional data 411 (first three-dimensional data),extracted three-dimensional data 412 (second three-dimensional data)having an amount of a feature greater than or equal to a threshold, andencodes extracted three-dimensional data 412 to generate encodedthree-dimensional data 414 (first encoded three-dimensional data).

This three-dimensional data encoding device 400 generates encodedthree-dimensional data 414 that is obtained by encoding data having anamount of a feature greater than or equal to the threshold. This reducesthe amount of data compared to the case where input three-dimensionaldata 411 is encoded as it is. Three-dimensional data encoding device 400is thus capable of reducing the amount of data to be transmitted.

Three-dimensional data encoding device 400 further encodes inputthree-dimensional data 411 to generate encoded three-dimensional data413 (second encoded three-dimensional data).

This three-dimensional data encoding device 400 enables selectivetransmission of encoded three-dimensional data 413 and encodedthree-dimensional data 414, in accordance, for example, with theintended use, etc.

Also, extracted three-dimensional data 412 is encoded by a firstencoding method, and input three-dimensional data 411 is encoded by asecond encoding method different from the first encoding method.

This three-dimensional data encoding device 400 enables the use of anencoding method suitable for each of input three-dimensional data 411and extracted three-dimensional data 412.

Also, of intra prediction and inter prediction, the inter prediction ismore preferentially performed in the first encoding method than in thesecond encoding method.

This three-dimensional data encoding device 400 enables inter predictionto be more preferentially performed on extracted three-dimensional data412 in which adjacent data items are likely to have low correlation.

Also, the first encoding method and the second encoding method representthree-dimensional positions differently. For example, the secondencoding method represents three-dimensional positions by octree, andthe first encoding method represents three-dimensional positions bythree-dimensional coordinates.

This three-dimensional data encoding device 400 enables the use of amore suitable method to represent the three-dimensional positions ofthree-dimensional data in consideration of the difference in the numberof data items (the number of VXLs or FVXLs) included.

Also, at least one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 includes an identifier indicating whether theencoded three-dimensional data is encoded three-dimensional dataobtained by encoding input three-dimensional data 411 or encodedthree-dimensional data obtained by encoding part of inputthree-dimensional data 411. Stated differently, such identifierindicates whether the encoded three-dimensional data is encodedthree-dimensional data 413 of a WLD or encoded three-dimensional data414 of a SWLD.

This enables the decoding device to readily judge whether the obtainedencoded three-dimensional data is encoded three-dimensional data 413 orencoded three-dimensional data 414.

Also, three-dimensional data encoding device 400 encodes extractedthree-dimensional data 412 in a manner that encoded three-dimensionaldata 414 has a smaller data amount than a data amount of encodedthree-dimensional data 413.

This three-dimensional data encoding device 400 enables encodedthree-dimensional data 414 to have a smaller data amount than the dataamount of encoded three-dimensional data 413.

Also, three-dimensional data encoding device 400 further extracts datacorresponding to an object having a predetermined attribute from inputthree-dimensional data 411 as extracted three-dimensional data 412. Theobject having a predetermined attribute is, for example, an objectnecessary for self-location estimation, driving assist, or self-driving,etc., or more specifically, a signal, an intersection, etc.

This three-dimensional data encoding device 400 is capable of generatingencoded three-dimensional data 414 that includes data required by thedecoding device.

Also, three-dimensional data encoding device 400 (server) further sends,to a client, one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 in accordance with a status of the client.

This three-dimensional data encoding device 400 is capable of sendingappropriate data in accordance with the status of the client.

Also, the status of the client includes one of a communication condition(e.g., network bandwidth) of the client and a traveling speed of theclient.

Also, three-dimensional data encoding device 400 further sends, to aclient, one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 in accordance with a request from the client.

This three-dimensional data encoding device 400 is capable of sendingappropriate data in accordance with the request from the client.

Also, three-dimensional data decoding device 500 according to thepresent embodiment decodes encoded three-dimensional data 413 or encodedthree-dimensional data 414 generated by three-dimensional data encodingdevice 400 described above.

Stated differently, three-dimensional data decoding device 500 decodes,by a first decoding method, encoded three-dimensional data 414 obtainedby encoding extracted three-dimensional data 412 having an amount of afeature greater than or equal to a threshold, extractedthree-dimensional data 412 having been extracted from inputthree-dimensional data 411.

Three-dimensional data decoding device 500 also decodes, by a seconddecoding method, encoded three-dimensional data 413 obtained by encodinginput three-dimensional data 411, the second decoding method beingdifferent from the first decoding method.

This three-dimensional data decoding device 500 enables selectivereception of encoded three-dimensional data 414 obtained by encodingdata having an amount of a feature greater than or equal to thethreshold and encoded three-dimensional data 413, in accordance, forexample, with the intended use, etc. Three-dimensional data decodingdevice 500 is thus capable of reducing the amount of data to betransmitted. Such three-dimensional data decoding device 500 furtherenables the use of a decoding method suitable for each of inputthree-dimensional data 411 and extracted three-dimensional data 412.

Also, of intra prediction and inter prediction, the inter prediction ismore preferentially performed in the first decoding method than in thesecond decoding method.

This three-dimensional data decoding device 500 enables inter predictionto be more preferentially performed on the extracted three-dimensionaldata in which adjacent data items are likely to have low correlation.

Also, the first decoding method and the second decoding method representthree-dimensional positions differently. For example, the seconddecoding method represents three-dimensional positions by octree, andthe first decoding method represents three-dimensional positions bythree-dimensional coordinates.

This three-dimensional data decoding device 500 enables the use of amore suitable method to represent the three-dimensional positions ofthree-dimensional data in consideration of the difference in the numberof data items (the number of VXLs or FVXLs) included.

Also, at least one of encoded three-dimensional data 413 and encodedthree-dimensional data 414 includes an identifier indicating whether theencoded three-dimensional data is encoded three-dimensional dataobtained by encoding input three-dimensional data 411 or encodedthree-dimensional data obtained by encoding part of inputthree-dimensional data 411.

Three-dimensional data decoding device 500 refers to such identifier inidentifying between encoded three-dimensional data 413 and encodedthree-dimensional data 414.

This three-dimensional data decoding device 500 is capable of readilyjudging whether the obtained encoded three-dimensional data is encodedthree-dimensional data 413 or encoded three-dimensional data 414.

Three-dimensional data decoding device 500 further notifies a server ofa status of the client (three-dimensional data decoding device 500).Three-dimensional data decoding device 500 receives one of encodedthree-dimensional data 413 and encoded three-dimensional data 414 fromthe server, in accordance with the status of the client.

This three-dimensional data decoding device 500 is capable of receivingappropriate data in accordance with the status of the client.

Also, the status of the client includes one of a communication condition(e.g., network bandwidth) of the client and a traveling speed of theclient.

Three-dimensional data decoding device 500 further makes a request ofthe server for one of encoded three-dimensional data 413 and encodedthree-dimensional data 414, and receives one of encodedthree-dimensional data 413 and encoded three-dimensional data 414 fromthe server, in accordance with the request.

This three-dimensional data decoding device 500 is capable of receivingappropriate data in accordance with the intended use.

Embodiment 3

The present embodiment will describe a method of transmitting/receivingthree-dimensional data between vehicles.

FIG. 24 is a schematic diagram showing three-dimensional data 607 beingtransmitted/received between own vehicle 600 and nearby vehicle 601.

In three-dimensional data that is obtained by a sensor mounted on ownvehicle 600 (e.g., a distance sensor such as a rangefinder, as well as astereo camera and a combination of a plurality of monocular cameras),there appears a region, three-dimensional data of which cannot becreated, due to an obstacle such as nearby vehicle 601, despite thatsuch region is included in sensor detection range 602 of own vehicle 600(such region is hereinafter referred to as occlusion region 604). Also,while the obtainment of three-dimensional data of a larger space enablesa higher accuracy of autonomous operations, a range of sensor detectiononly by own vehicle 600 is limited.

Sensor detection range 602 of own vehicle 600 includes region 603,three-dimensional data of which is obtainable, and occlusion region 604.A range, three-dimensional data of which own vehicle 600 wishes toobtain, includes sensor detection range 602 of own vehicle 600 and otherregions. Sensor detection range 605 of nearby vehicle 601 includesocclusion region 604 and region 606 that is not included in sensordetection range 602 of own vehicle 600.

Nearby vehicle 601 transmits information detected by nearby vehicle 601to own vehicle 600. Own vehicle 600 obtains the information detected bynearby vehicle 601, such as a preceding vehicle, thereby obtainingthree-dimensional data 607 of occlusion region 604 and region 606outside of sensor detection range 602 of own vehicle 600. Own vehicle600 uses the information obtained by nearby vehicle 601 to complementthe three-dimensional data of occlusion region 604 and region 606outside of the sensor detection range.

The usage of three-dimensional data in autonomous operations of avehicle or a robot includes self-location estimation, detection ofsurrounding conditions, or both. For example, for self-locationestimation, three-dimensional data is used that is generated by ownvehicle 600 on the basis of sensor information of own vehicle 600. Fordetection of surrounding conditions, three-dimensional data obtainedfrom nearby vehicle 601 is also used in addition to thethree-dimensional data generated by own vehicle 600.

Nearby vehicle 601 that transmits three-dimensional data 607 to ownvehicle 600 may be determined in accordance with the state of ownvehicle 600. For example, the current nearby vehicle 601 is a precedingvehicle when own vehicle 600 is running straight ahead, an oncomingvehicle when own vehicle 600 is turning right, and a following vehiclewhen own vehicle 600 is rolling backward. Alternatively, the driver ofown vehicle 600 may directly specify nearby vehicle 601 that transmitsthree-dimensional data 607 to own vehicle 600.

Alternatively, own vehicle 600 may search for nearby vehicle 601 havingthree-dimensional data of a region that is included in a space,three-dimensional data of which own vehicle 600 wishes to obtain, andthat own vehicle 600 cannot obtain. The region own vehicle 600 cannotobtain is occlusion region 604, or region 606 outside of sensordetection range 602, etc.

Own vehicle 600 may identify occlusion region 604 on the basis of thesensor information of own vehicle 600. For example, own vehicle 600identifies, as occlusion region 604, a region which is included insensor detection range 602 of own vehicle 600, and three-dimensionaldata of which cannot be created.

The following describes example operations to be performed when avehicle that transmits three-dimensional data 607 is a precedingvehicle. FIG. 25 is a diagram showing an example of three-dimensionaldata to be transmitted in such case.

As FIG. 25 shows, three-dimensional data 607 transmitted from thepreceding vehicle is, for example, a sparse world (SWLD) of a pointcloud. Stated differently, the preceding vehicle createsthree-dimensional data (point cloud) of a WLD from information detectedby a sensor of such preceding vehicle, and extracts data having anamount of features greater than or equal to the threshold from suchthree-dimensional data of the WLD, thereby creating three-dimensionaldata (point cloud) of the SWLD. Subsequently, the preceding vehicletransmits the created three-dimensional data of the SWLD to own vehicle600.

Own vehicle 600 receives the SWLD, and merges the received SWLD with thepoint cloud created by own vehicle 600.

The SWLD to be transmitted includes information on the absolutecoordinates (the position of the SWLD in the coordinates system of athree-dimensional map). The merge is achieved by own vehicle 600overwriting the point cloud generated by own vehicle 600 on the basis ofsuch absolute coordinates.

The SWLD transmitted from nearby vehicle 601 may be: a SWLD of region606 that is outside of sensor detection range 602 of own vehicle 600 andwithin sensor detection range 605 of nearby vehicle 601; or a SWLD ofocclusion region 604 of own vehicle 600; or the SWLDs of the both. Ofthese SWLDs, a SWLD to be transmitted may also be a SWLD of a regionused by nearby vehicle 601 to detect the surrounding conditions.

Nearby vehicle 601 may change the density of a point cloud to transmit,in accordance with the communication available time, during which ownvehicle 600 and nearby vehicle 601 can communicate, and which is basedon the speed difference between these vehicles. For example, when thespeed difference is large and the communication available time is short,nearby vehicle 601 may extract three-dimensional points having a largeamount of features from the SWLD to decrease the density (data amount)of the point cloud.

The detection of the surrounding conditions refers to judging thepresence/absence of persons, vehicles, equipment for roadworks, etc.,identifying their types, and detecting their positions, travellingdirections, traveling speeds, etc.

Own vehicle 600 may obtain braking information of nearby vehicle 601instead of or in addition to three-dimensional data 607 generated bynearby vehicle 601. Here, the braking information of nearby vehicle 601is, for example, information indicating that the accelerator or thebrake of nearby vehicle 601 has been pressed, or the degree of suchpressing.

In the point clouds generated by the vehicles, the three-dimensionalspaces are segmented on a random access unit, in consideration oflow-latency communication between the vehicles. Meanwhile, in athree-dimensional map, etc., which is map data downloaded from theserver, a three-dimensional space is segmented in a larger random accessunit than in the case of inter-vehicle communication.

Data on a region that is likely to be an occlusion region, such as aregion in front of the preceding vehicle and a region behind thefollowing vehicle, is segmented on a finer random access unit aslow-latency data.

Data on a region in front of a vehicle has an increased importance whenon an expressway, and thus each vehicle creates a SWLD of a range with anarrowed viewing angle on a finer random access unit when running on anexpressway.

When the SWLD created by the preceding vehicle for transmission includesa region, the point cloud of which own vehicle 600 can obtain, thepreceding vehicle may remove the point cloud of such region to reducethe amount of data to transmit.

Next, the structure and operations of three-dimensional data creationdevice 620 will be described, which is the three-dimensional datareception device according to the present embodiment.

FIG. 26 is a block diagram of three-dimensional data creation device 620according to the present embodiment. Such three-dimensional datacreation device 620, which is included, for example, in theabove-described own vehicle 600, mergers first three-dimensional data632 created by three-dimensional data creation device 620 with thereceived second three-dimensional data 635, thereby creating thirdthree-dimensional data 636 having a higher density.

Such three-dimensional data creation device 620 includesthree-dimensional data creator 621, request range determiner 622,searcher 623, receiver 624, decoder 625, and merger 626. FIG. 27 is aflowchart of operations performed by three-dimensional data creationdevice 620.

First, three-dimensional data creator 621 creates firstthree-dimensional data 632 by use of sensor information 631 detected bythe sensor included in own vehicle 600 (S621). Next, request rangedeterminer 622 determines a request range, which is the range of athree-dimensional space, the data on which is insufficient in thecreated first three-dimensional data 632 (S622).

Next, searcher 623 searches for nearby vehicle 601 having thethree-dimensional data of the request range, and sends request rangeinformation 633 indicating the request range to nearby vehicle 601having been searched out (S623). Next, receiver 624 receives encodedthree-dimensional data 634, which is an encoded stream of the requestrange, from nearby vehicle 601 (S624). Note that searcher 623 mayindiscriminately send requests to all vehicles included in a specifiedrange to receive encoded three-dimensional data 634 from a vehicle thathas responded to the request. Searcher 623 may send a request not onlyto vehicles but also to an object such as a signal and a sign, andreceive encoded three-dimensional data 634 from the object.

Next, decoder 625 decodes the received encoded three-dimensional data634, thereby obtaining second three-dimensional data 635 (S625). Next,merger 626 merges first three-dimensional data 632 with secondthree-dimensional data 635, thereby creating three-dimensional data 636having a higher density (S626).

Next, the structure and operations of three-dimensional datatransmission device 640 according to the present embodiment will bedescribed. FIG. 28 is a block diagram of three-dimensional datatransmission device 640.

Three-dimensional data transmission device 640 is included, for example,in the above-described nearby vehicle 601. Three-dimensional datatransmission device 640 processes fifth three-dimensional data 652created by nearby vehicle 601 into sixth three-dimensional data 654requested by own vehicle 600, encodes sixth three-dimensional data 654to generate encoded three-dimensional data 634, and sends encodedthree-dimensional data 634 to own vehicle 600.

Three-dimensional data transmission device 640 includesthree-dimensional data creator 641, receiver 642, extractor 643, encoder644, and transmitter 645. FIG. 29 is a flowchart of operations performedby three-dimensional data transmission device 640.

First, three-dimensional data creator 641 creates fifththree-dimensional data 652 by use of sensor information 651 detected bythe sensor included in nearby vehicle 601 (S641). Next, receiver 642receives request range information 633 from own vehicle 600 (S642).

Next, extractor 643 extracts from fifth three-dimensional data 652 thethree-dimensional data of the request range indicated by request rangeinformation 633, thereby processing fifth three-dimensional data 652into sixth three-dimensional data 654 (S643). Next, encoder 644 encodessixth three-dimensional data 654 to generate encoded three-dimensionaldata 643, which is an encoded stream (S644). Then, transmitter 645 sendsencoded three-dimensional data 634 to own vehicle 600 (S645).

Note that although an example case is described here in which ownvehicle 600 includes three-dimensional data creation device 620 andnearby vehicle 601 includes three-dimensional data transmission device640, each of the vehicles may include the functionality of boththree-dimensional data creation device 620 and three-dimensional datatransmission device 640.

The following describes the structure and operations ofthree-dimensional data creation device 620 when three-dimensional datacreation device 620 is a surrounding condition detection device thatenables the detection of the surrounding conditions of own vehicle 600.FIG. 30 is a block diagram of the structure of three-dimensional datacreation device 620A in such case. Three-dimensional data creationdevice 620A shown in FIG. 30 further includes detection regiondeterminer 627, surrounding condition detector 628, and autonomousoperation controller 629, in addition to the components ofthree-dimensional data creation device 620 shown in FIG. 26.Three-dimensional data creation device 620A is included in own vehicle600.

FIG. 31 is a flowchart of processes, performed by three-dimensional datacreation device 620A, of detecting the surrounding conditions of ownvehicle 600.

First, three-dimensional data creator 621 creates firstthree-dimensional data 632, which is a point cloud, by use of sensorinformation 631 on the detection range of own vehicle 600 detected bythe sensor of own vehicle 600 (S661). Note that three-dimensional datacreation device 620A may further estimate the self-location by use ofsensor information 631.

Next, detection region determiner 627 determines a target detectionrange, which is a spatial region, the surrounding conditions of whichare wished to be detected (S662). For example, detection regiondeterminer 627 calculates a region that is necessary for the detectionof the surrounding conditions, which is an operation required for safeautonomous operations (self-driving), in accordance with the conditionsof autonomous operations, such as the direction and speed of travelingof own vehicle 600, and determines such region as the target detectionrange.

Next, request range determiner 622 determines, as a request range,occlusion region 604 and a spatial region that is outside of thedetection range of the sensor of own vehicle 600 but that is necessaryfor the detection of the surrounding conditions (S663).

When the request range determined in step S663 is present (Yes in S664),searcher 623 searches for a nearby vehicle having information on therequest range. For example, searcher 623 may inquire about whether anearby vehicle has information on the request range, or may judgewhether a nearby vehicle has information on the request range, on thebasis of the positions of the request range and such nearby vehicle.Next, searcher 623 sends, to nearby vehicle 601 having been searchedout, request signal 637 that requests for the transmission ofthree-dimensional data. Searcher 623 then receives an acceptance signalfrom nearby vehicle 601 indicating that the request of request signal637 has been accepted, after which searcher 623 sends request rangeinformation 633 indicating the request range to nearby vehicle 601(S665).

Next, receiver 624 detects a notice that transmission data 638 has beentransmitted, which is the information on the request range, and receivessuch transmission data 638 (S666).

Note that three-dimensional data creation device 620A mayindiscriminately send requests to all vehicles in a specified range andreceive transmission data 638 from a vehicle that has sent a responseindicating that such vehicle has the information on the request range,without searching for a vehicle to send a request to. Searcher 623 maysend a request not only to vehicles but also to an object such as asignal and a sign, and receive transmission data 638 from such object.

Transmission data 638 includes at least one of the following generatedby nearby vehicle 601: encoded three-dimensional data 634, which isencoded three-dimensional data of the request range; and surroundingcondition detection result 639 of the request range. Surroundingcondition detection result 639 indicates the positions, travelingdirections and traveling speeds, etc., of persons and vehicles detectedby nearby vehicle 601. Transmission data 638 may also includeinformation indicating the position, motion, etc., of nearby vehicle601. For example, transmission data 638 may include braking informationof nearby vehicle 601.

When the received transmission data 638 includes encodedthree-dimensional data 634 (Yes in 667), decoder 625 decodes encodedthree-dimensional data 634 to obtain second three-dimensional data 635of the SWLD (S668). Stated differently, second three-dimensional data635 is three-dimensional data (SWLD) that has been generated byextracting data having an amount of features greater than or equal tothe threshold from fourth three-dimensional data (WLD).

Next, merger 626 merges first three-dimensional data 632 with secondthree-dimensional data 635, thereby generating third three-dimensionaldata 636 (S669).

Next, surrounding condition detector 628 detects the surroundingconditions of own vehicle 600 by use of third three-dimensional data636, which is a point cloud of a spatial region necessary to detect thesurrounding conditions (S670). Note that when the received transmissiondata 638 includes surrounding condition detection result 639,surrounding condition detector 628 detects the surrounding conditions ofown vehicle 600 by use of surrounding condition detection result 639, inaddition to third three-dimensional data 636. When the receivedtransmission data 638 includes the braking information of nearby vehicle601, surrounding condition detector 628 detects the surroundingconditions of own vehicle 600 by use of such braking information, inaddition to third three-dimensional data 636.

Next, autonomous operation controller 629 controls the autonomousoperations (self-driving) of own vehicle 600 on the basis of thesurrounding condition detection result obtained by surrounding conditiondetector 628 (S671). Note that the surrounding condition detectionresult may be presented to the driver via a user interface (UI), etc.

Meanwhile, when the request range is not present in step S663 (No inS664), or stated differently, when information on all spatial regionsnecessary to detect the surrounding conditions has been created on thebasis of sensor information 631, surrounding condition detector 628detects the surrounding conditions of own vehicle 600 by use of firstthree-dimensional data 632, which is the point cloud of the spatialregion necessary to detect the surrounding conditions (S672). Then,autonomous operation controller 629 controls the autonomous operations(self-driving) of own vehicle 600 on the basis of the surroundingcondition detection result obtained by surrounding condition detector628 (S671).

Meanwhile, when the received transmission data 638 does not includeencoded three-dimensional data 634 (No in S667), or stated differently,when transmission data 638 includes only surrounding condition detectionresult 639 or the braking information of nearby vehicle 601, surroundingcondition detector 628 detects the surrounding conditions of own vehicle600 by use of first three-dimensional data 632, and surroundingcondition detection result 639 or the braking information (S673). Then,autonomous operation controller 629 controls the autonomous operations(self-driving) of own vehicle 600 on the basis of the surroundingcondition detection result obtained by surrounding condition detector628 (S671).

Next, three-dimensional data transmission device 640A will be describedthat transmits transmission data 638 to the above-describedthree-dimensional data creation device 620A. FIG. 32 is a block diagramof such three-dimensional data transmission device 640A.

Three-dimensional data transmission device 640A shown in FIG. 32 furtherincludes transmission permissibility judgment unit 646, in addition tothe components of three-dimensional data transmission device 640 shownin FIG. 28. Three-dimensional data transmission device 640A is includedin nearby vehicle 601.

FIG. 33 is a flowchart of example operations performed bythree-dimensional data transmission device 640A. First,three-dimensional data creator 641 creates fifth three-dimensional data652 by use of sensor information 651 detected by the sensor included innearby vehicle 601 (S681).

Next, receiver 642 receives from own vehicle 600 request signal 637 thatrequests for the transmission of three-dimensional data (S682). Next,transmission permissibility judgment unit 646 determines whether toaccept the request indicated by request signal 637 (S683). For example,transmission permissibility judgment unit 646 determines whether toaccept the request on the basis of the details previously set by theuser. Note that receiver 642 may receive a request from the other endsuch as a request range beforehand, and transmission permissibilityjudgment unit 646 may determine whether to accept the request inaccordance with the details of such request. For example, transmissionpermissibility judgment unit 646 may determine to accept the requestwhen the three-dimensional data transmission device has thethree-dimensional data of the request range, and not to accept therequest when the three-dimensional data transmission device does nothave the three-dimensional data of the request range.

When determining to accept the request (Yes in S683), three-dimensionaldata transmission device 640A sends a permission signal to own vehicle600, and receiver 642 receives request range information 633 indicatingthe request range (S684). Next, extractor 643 extracts the point cloudof the request range from fifth three-dimensional data 652, which is apoint cloud, and creates transmission data 638 that includes sixththree-dimensional data 654, which is the SWLD of the extracted pointcloud (S685).

Stated differently, three-dimensional data transmission device 640Acreates seventh three-dimensional data (WLD) from sensor information651, and extracts data having an amount of features greater than orequal to the threshold from seventh three-dimensional data (WLD),thereby creating fifth three-dimensional data 652 (SWLD). Note thatthree-dimensional data creator 641 may create three-dimensional data ofa SWLD beforehand, from which extractor 643 may extractthree-dimensional data of a SWLD of the request range. Alternatively,extractor 643 may generate three-dimensional data of the SWLD of therequest range from the three-dimensional data of the WLD of the requestrange.

Transmission data 638 may include surrounding condition detection result639 of the request range obtained by nearby vehicle 601 and the brakinginformation of nearby vehicle 601. Transmission data 638 may includeonly at least one of surrounding condition detection result 639 of therequest range obtained by nearby vehicle 601 and the braking informationof nearby vehicle 601, without including sixth three-dimensional data654.

When transmission data 638 includes sixth three-dimensional data 654(Yes in S686), encoder 644 encodes sixth three-dimensional data 654 togenerate encoded three-dimensional data 634 (S687).

Then, transmitter 645 sends to own vehicle 600 transmission data 638that includes encoded three-dimensional data 634 (S688).

Meanwhile, when transmission data 638 does not include sixththree-dimensional data 654 (No in S686), transmitter 645 sends to ownvehicle 600 transmission data 638 that includes at least one ofsurrounding condition detection result 639 of the request range obtainedby nearby vehicle 601 and the braking information of nearby vehicle 601(S688).

The following describes variations of the present embodiment.

For example, information transmitted from nearby vehicle 601 may not bethree-dimensional data or a surrounding condition detection resultgenerated by the nearby vehicle, and thus may be accurate keypointinformation on nearby vehicle 601 itself. Own vehicle 600 correctskeypoint information on the preceding vehicle in the point cloudobtained by own vehicle 600 by use of such keypoint information ofnearby vehicle 601. This enables own vehicle 600 to increase thematching accuracy at the time of self-location estimation.

The keypoint information of the preceding vehicle is, for example,three-dimensional point information that includes color information andcoordinates information. This allows for the use of the keypointinformation of the preceding vehicle independently of the type of thesensor of own vehicle 600, i.e., regardless of whether the sensor is alaser sensor or a stereo camera.

Own vehicle 600 may use the point cloud of a SWLD not only at the timeof transmission, but also at the time of calculating the accuracy ofself-location estimation. For example, when the sensor of own vehicle600 is an imaging device such as a stereo camera, own vehicle 600detects two-dimensional points on an image captured by the camera of ownvehicle 600, and uses such two-dimensional points to estimate theself-location. Own vehicle 600 also creates a point cloud of a nearbyobject at the same time of estimating the self-location. Own vehicle 600re-projects the three-dimensional points of the SWLD included in thepoint cloud onto the two-dimensional image, and evaluates the accuracyof self-location estimation on the basis of an error between thedetected points and the re-projected points on the two-dimensionalimage.

When the sensor of own vehicle 600 is a laser sensor such as a LIDAR,own vehicle 600 evaluates the accuracy of self-location estimation onthe basis of an error calculated by Interactive Closest Point algorithmby use of the SWLD of the created point cloud of and the SWLD of thethree-dimensional map.

When a communication state via a base station or a server is poor in,for example, a 5G environment, own vehicle 600 may obtain athree-dimensional map from nearby vehicle 601.

Also, own vehicle 600 may obtain information on a remote region thatcannot be obtained from a nearby vehicle, over inter-vehiclecommunication. For example, own vehicle 600 may obtain information on atraffic accident, etc. that has just occurred at a few hundred meters ora few kilometers away from own vehicle 600 from an oncoming vehicle overa passing communication, or by a relay system in which information issequentially passed to nearby vehicles. Here, the data format of thedata to be transmitted is transmitted as meta-information in an upperlayer of a dynamic three-dimensional map.

The result of detecting the surrounding conditions and the informationdetected by own vehicle 600 may be presented to the user via a UI. Thepresentation of such information is achieved, for example, bysuperimposing the information onto the screen of the car navigationsystem or the front window.

In the case of a vehicle not supporting self-driving but having thefunctionality of cruise control, the vehicle may identify a nearbyvehicle traveling in the self-driving mode, and track such nearbyvehicle.

Own vehicle 600 may switch the operation mode from the self-driving modeto the tracking mode to track a nearby vehicle, when failing to estimatethe self-location for the reason such as failing to obtain athree-dimensional map or having too large a number of occlusion regions.

Meanwhile, a vehicle to be tracked may include a UI which warns the userof that the vehicle is being tracked and by which the user can specifywhether to permit tracking. In this case, a system may be provided inwhich, for example, an advertisement is displayed to the vehicle that istracking and an incentive is given to the vehicle that is being tracked.

The information to be transmitted is basically a SWLD beingthree-dimensional data, but may also be information that is inaccordance with request settings set in own vehicle 600 or publicsettings set in a preceding vehicle. For example, the information to betransmitted may be a WLD being a dense point cloud, the detection resultof the surrounding conditions obtained by the preceding vehicle, or thebraking information of the preceding vehicle.

Own vehicle 600 may also receive a WLD, visualize the three-dimensionaldata of the WLD, and present such visualized three-dimensional data tothe driver by use of a GUI. In so doing, own vehicle 600 may present thethree-dimensional data in which information is color-coded, for example,so that the user can distinguish between the point cloud created by ownvehicle 600 and the received point cloud.

When presenting the information detected by own vehicle 600 and thedetection result of nearby vehicle 601 to the driver via the GUI, ownvehicle 600 may present the information in which information iscolor-coded, for example, so that the user can distinguish between theinformation detected by own vehicle 600 and the received detectionresult.

As described above, in three-dimensional data creation device 620according to the present embodiment, three-dimensional data creator 621creates first three-dimensional data 632 from sensor information 631detected by a sensor. Receiver 624 receives encoded three-dimensionaldata 634 that is obtained by encoding second three-dimensional data 635.Decoder 625 decodes received encoded three-dimensional data 634 toobtain second three-dimensional data 635. Merger 626 merges firstthree-dimensional data 632 with second three-dimensional data 635 tocreate third three-dimensional data 636.

Such three-dimensional data creation device 620 is capable of creatingdetailed third three-dimensional data 636 by use of created firstthree-dimensional data 632 and received second three-dimensional data635.

Also, merger 626 merges first three-dimensional data 632 with secondthree-dimensional data 635 to create third three-dimensional data 636that is denser than first three-dimensional data 632 and secondthree-dimensional data 635.

Second three-dimensional data 635 (e.g., SWLD) is three-dimensional datathat is generated by extracting, from fourth three-dimensional data(e.g., WLD), data having an amount of a feature greater than or equal tothe threshold.

Such three-dimensional data creation device 620 reduces the amount ofthree-dimensional data to be transmitted.

Three-dimensional data creation device 620 further includes searcher 623that searches for a transmission device that transmits encodedthree-dimensional data 634. Receiver 624 receives encodedthree-dimensional data 634 from the transmission device that has beensearched out.

Such three-dimensional data creation device 620 is, for example, capableof searching for a transmission device having necessarythree-dimensional data.

Such three-dimensional data creation device further includes requestrange determiner 622 that determines a request range that is a range ofa three-dimensional space, the three-dimensional of which is requested.Searcher 623 transmits request range information 633 indicating therequest range to the transmission device. Second three-dimensional data635 includes the three-dimensional data of the request range.

Such three-dimensional data creation device 620 is capable of receivingnecessary three-dimensional data, while reducing the amount ofthree-dimensional data to be transmitted.

Also, request range determiner 622 determines, as the request range, aspatial range that includes occlusion region 604 undetectable by thesensor.

Also, in three-dimensional data transmission device 640 according to thepresent embodiment, three-dimensional data creator 641 creates fifththree-dimensional data 652 from sensor information 651 detected by thesensor. Extractor 643 extracts part of fifth three-dimensional data 652to create sixth three-dimensional data 654. Encoder 644 encodes sixththree-dimensional data 654 to generate encoded three-dimensional data634. Transmitter 645 transmits encoded three-dimensional data 634.

Such three-dimensional data transmission device 640 is capable oftransmitting self-created three-dimensional data to another device,while reducing the amount of three-dimensional data to be transmitted.

Also, three-dimensional data creator 641 creates sevenththree-dimensional data (e.g., WLD) from sensor information 651 detectedby the sensor, and extracts, from the seventh three-dimensional data,data having an amount of a feature greater than or equal to thethreshold, to create fifth three-dimensional data 652 (e.g., SWLD).

Such three-dimensional data creation device 640 reduces the amount ofthree-dimensional data to be transmitted.

Three-dimensional data transmission device 640 further includes receiver642 that receives, from the reception device, request range information633 indicating the request range that is the range of athree-dimensional space, the three-dimensional data of which isrequested. Extractor 643 extracts the three-dimensional data of therequest range from fifth three-dimensional data 652 to create sixththree-dimensional data 654. Transmitter 645 transmits encodedthree-dimensional data 634 to the reception device.

Such three-dimensional data transmission device 640 reduces the amountof three-dimensional data to be transmitted.

Embodiment 4

The present embodiment describes operations performed in abnormal caseswhen self-location estimation is performed on the basis of athree-dimensional map.

A three-dimensional map is expected to find its expanded use inself-driving of a vehicle and autonomous movement, etc. of a mobileobject such as a robot and a flying object (e.g., a drone). Examplemeans for enabling such autonomous movement include a method in which amobile object travels in accordance with a three-dimensional map, whileestimating its own location on the map (self-location estimation).

The self-location estimation is enabled by matching a three-dimensionalmap with three-dimensional information on the surrounding of the ownvehicle (hereinafter referred to as self-detected three-dimensionaldata) obtained by a sensor equipped in the own vehicle, such as arangefinder (e.g., a LiDAR) and a stereo camera to estimate the locationof the own vehicle on the three-dimensional map.

As in the case of an HD map suggested by HERE Technologies, for example,a three-dimensional map may include not only a three-dimensional pointcloud, but also two-dimensional map data such as information on theshapes of roads and intersections, or information that changes inreal-time such as information on a traffic jam and an accident. Athree-dimensional map includes a plurality of layers such as layers ofthree-dimensional data, two-dimensional data, and meta-data that changesin real-time, from among which the device can obtain or refer to onlynecessary data.

Point cloud data may be a SWLD as described above, or may include pointgroup data that is different from keypoints. The transmission/receptionof point cloud data is basically carried out in one or more randomaccess units.

A method described below is used as a method of matching athree-dimensional map with self-detected three-dimensional data. Forexample, the device compares the shapes of the point groups in eachother's point clouds, and determines that portions having a high degreeof similarity among keypoints correspond to the same position. When thethree-dimensional map is formed by a SWLD, the device also performsmatching by comparing the keypoints that form the SWLD withthree-dimensional keypoints extracted from the self-detectedthree-dimensional data.

Here, to enable highly accurate self-location estimation, the followingneeds to be satisfied: (A) the three-dimensional map and theself-detected three-dimensional data have been already obtained; and (B)their accuracies satisfy a predetermined requirement. However, one of(A) and (B) cannot be satisfied in abnormal cases such as ones describedbelow.

1. A three-dimensional map is unobtainable over communication.

2. A three-dimensional map is not present, or a three-dimensional maphaving been obtained is corrupt.

3. A sensor of the own vehicle has trouble, or the accuracy of thegenerated self-detected three-dimensional data is inadequate due to badweather.

The following describes operations to cope with such abnormal cases. Thefollowing description illustrates an example case of a vehicle, but themethod described below is applicable to mobile objects on the whole thatare capable of autonomous movement, such as a robot and a drone.

The following describes the structure of the three-dimensionalinformation processing device and its operation according to the presentembodiment capable of coping with abnormal cases regarding athree-dimensional map or self-detected three-dimensional data. FIG. 34is a block diagram of an example structure of three-dimensionalinformation processing device 700 according to the present embodiment.FIG. 35 is a flowchart of a three-dimensional information processingmethod performed by three-dimensional information processing device 700.

Three-dimensional information processing device 700 is equipped, forexample, in a mobile object such as a vehicle. As shown in FIG. 34,three-dimensional information processing device 700 includesthree-dimensional map obtainer 701, self-detected data obtainer 702,abnormal case judgment unit 703, coping operation determiner 704, andoperation controller 705.

Note that three-dimensional information processing device 700 mayinclude a non-illustrated two-dimensional or one-dimensional sensor thatdetects a structural object or a mobile object around the own vehicle,such as a camera capable of obtaining two-dimensional images and asensor for one-dimensional data utilizing ultrasonic or laser.Three-dimensional information processing device 700 may also include anon-illustrated communication unit that obtains a three-dimensional mapover a mobile communication network, such as 4G and 5G, or viainter-vehicle communication or road-to-vehicle communication.

As shown in FIG. 35, three-dimensional map obtainer 701 obtainsthree-dimensional map 711 of the surroundings of the traveling route(S701). For example, three-dimensional map obtainer 701 obtainsthree-dimensional map 711 over a mobile communication network, or viainter-vehicle communication or road-to-vehicle communication.

Next, self-detected data obtainer 702 obtains self-detectedthree-dimensional data 712 on the basis of sensor information (S702).For example, self-detected data obtainer 702 generates self-detectedthree-dimensional data 712 on the basis of the sensor informationobtained by a sensor equipped in the own vehicle.

Next, abnormal case judgment unit 703 conducts a predetermined check ofat least one of obtained three-dimensional map 711 and self-detectedthree-dimensional data 712 to detect an abnormal case (S703). Stateddifferently, abnormal case judgment unit 703 judges whether at least oneof obtained three-dimensional map 711 and self-detectedthree-dimensional data 712 is abnormal.

When the abnormal case is detected in step S703 (Yes in S704), copingoperation determiner 704 determines a coping operation to cope with suchabnormal case (S705). Next, operation controller 705 controls theoperation of each of the processing units necessary to perform thecoping operation (S706).

Meanwhile, when no abnormal case is detected in step S703 (No in S704),three-dimensional information processing device 700 terminates theprocess.

Also, three-dimensional information processing device 700 estimates thelocation of the vehicle equipped with three-dimensional informationprocessing device 700, using three-dimensional map 711 and self-detectedthree-dimensional data 712. Next, three-dimensional informationprocessing device 700 performs the automatic operation of the vehicle byuse of the estimated location of the vehicle.

As described above, three-dimensional information processing device 700obtains, via a communication channel, map data (three-dimensional map711) that includes first three-dimensional position information. Thefirst three-dimensional position information includes, for example, aplurality of random access units, each of which is an assembly of atleast one subspace and is individually decodable, the at least onesubspace having three-dimensional coordinates information and serving asa unit in which each of the plurality of random access units is encoded.The first three-dimensional position information is, for example, data(SWLD) obtained by encoding keypoints, each of which has an amount of athree-dimensional feature greater than or equal to a predeterminedthreshold.

Three-dimensional information processing device 700 also generatessecond three-dimensional position information (self-detectedthree-dimensional data 712) from information detected by a sensor.Three-dimensional information processing device 700 then judges whetherone of the first three-dimensional position information and the secondthree-dimensional position information is abnormal by performing, on oneof the first three-dimensional position information and the secondthree-dimensional position information, a process of judging whether anabnormality is present.

Three-dimensional information processing device 700 determines a copingoperation to cope with the abnormality when one of the firstthree-dimensional position information and the second three-dimensionalposition information is judged to be abnormal. Three-dimensionalinformation processing device 700 then executes a control that isrequired to perform the coping operation.

This structure enables three-dimensional information processing device700 to detect an abnormality regarding one of the firstthree-dimensional position information and the second three-dimensionalposition information, and to perform a coping operation therefor.

The following describes coping operations used for the abnormal case 1in which three-dimensional map 711 is unobtainable via communication.

Three-dimensional map 711 is necessary to perform self-locationestimation, and thus the vehicle needs to obtain three-dimensional map711 via communication when not having obtained in advancethree-dimensional map 711 corresponding to the route to the destination.In some cases, however, the vehicle cannot obtain three-dimensional map711 of the traveling route due to a reason such as a congestedcommunication channel and a deteriorated environment of radio wavereception.

Abnormal case judgment unit 703 judges whether three-dimensional map 711of the entire section on the route to the destination or a sectionwithin a predetermined range from the current position has already beenobtained, and judges that the current condition applies to the abnormalcase 1 when three-dimensional map 711 has not been obtained yet. Stateddifferently, abnormal case judgment unit 703 judges whetherthree-dimensional map 711 (the first three-dimensional positioninformation) is obtainable via a communication channel, and judges thatthree-dimensional map 711 is abnormal when three-dimensional map 711 isunobtainable via a communication channel.

When the current condition is judged to be the abnormal case 1, copingoperation determiner 704 selects one of the two types of copingoperations: (1) continue the self-location estimation; and (2) terminatethe self-location estimation.

First, a specific example of the coping operation to continue theself-location estimation will be described. Three-dimensional map 711 ofthe route to the destination is necessary to continue the self-locationestimation.

For example, the vehicle identifies a place, within the range ofthree-dimensional map 711 having been obtained, in which the use of acommunication channel is possible. The vehicle moves to such identifiedplace, and obtains three-dimensional map 711. Here, the vehicle mayobtain the whole three-dimensional map 711 to the destination, or mayobtain three-dimensional map 711 on random access units within the upperlimit capacity of a storage of the own vehicle, such as a memory and anHDD.

Note that the vehicle may separately obtain communication conditions onthe route, and when the communication conditions on the route arepredicted to be poor, the vehicle may obtain in advancethree-dimensional map 711 of a section in which communication conditionsare predicted to be poor, before arriving at such section, or obtain inadvance three-dimensional map 711 of the maximum range obtainable.Stated differently, three-dimensional information processing device 700predicts whether the vehicle will enter an area in which communicationconditions are poor. When the vehicle is predicted to enter an area inwhich communication conditions are poor, three-dimensional informationprocessing device 700 obtains three-dimensional map 711 before thevehicle enters such area.

Alternatively, the vehicle may identify a random access unit that formsthe minimum three-dimensional map 711, the range of which is narrowerthan that of the normal times, required to estimate the location of thevehicle on the route, and receive a random access unit having beenidentified. Stated differently, three-dimensional information processingdevice 700 may obtain, via a communication channel, thirdthree-dimensional position information having a narrower range than therange of the first three-dimensional position information, whenthree-dimensional map 711 (the first three-dimensional positioninformation) is unobtainable via the communication channel.

Also, when being unable to access a server that distributesthree-dimensional map 711, the vehicle may obtain three-dimensional map711 from a mobile object that has already obtained three-dimensional map711 of the route to the destination and that is capable of communicatingwith the own vehicle, such as another vehicle traveling around the ownvehicle.

Next, a specific example of the coping operation to terminate theself-location estimation will be described. Three-dimensional map 711 ofthe route to the destination is unnecessary in this case.

For example, the vehicle notifies the driver of that the vehicle cannotmaintain the functionally of automatic operation, etc. that is performedon the basis of the self-location estimation, and shifts the operationmode to a manual mode in which the driver operates the vehicle.

Automatic operation is typically carried out when self-locationestimation is performed, although there may be a difference in the levelof automatic operation in accordance with the degree of humaninvolvement. Meanwhile, the estimated location of the vehicle can alsobe used as navigation information, etc. when the vehicle is operated bya human, and thus the estimated location of the vehicle is notnecessarily used for automatic operation.

Also, when being unable to use a communication channel that the vehicleusually uses, such as a mobile communication network (e.g., 4G and 5G),the vehicle checks whether three-dimensional map 711 is obtainable viaanother communication channel, such as road-to-vehicle Wi-Fi (registeredtrademark) or millimeter-wave communication, or inter-vehiclecommunication, and switches to one of these communication channels viawhich three-dimensional map 711 is obtainable.

When being unable to obtain three-dimensional map 711, the vehicle mayobtain a two-dimensional map to continue automatic operation by use ofsuch two-dimensional map and self-detected three-dimensional data 712.Stated differently, when being unable to obtain three-dimensional map711 via a communication channel, three-dimensional informationprocessing device 700 may obtain, via a communication channel, map datathat includes two-dimensional position information (a two-dimensionalmap) to estimate the location of the vehicle by use of thetwo-dimensional position information and self-detected three-dimensionaldata 712.

More specifically, the vehicle uses the two-dimensional map andself-detected three-dimensional data 712 to estimate its own location,and uses self-detected three-dimensional data 712 to detect a vehicle, apedestrian, an obstacle, etc. around the own vehicle.

Here, the map data such as an HD map is capable of including, togetherwith three-dimensional map 711 formed by a three-dimensional pointcloud: two-dimensional map data (a two-dimensional map); simplified mapdata obtained by extracting, from the two-dimensional map data,characteristic information such as a road shape and an intersection; andmeta-data representing real-time information such as a traffic jam, anaccident, and a roadwork. For example, the map data has a layerstructure in which three-dimensional data (three-dimensional map 711),two-dimensional data (a two-dimensional map), and meta-data are disposedfrom the bottom layer in the stated order.

Here, the two-dimensional data is smaller in data size than thethree-dimensional data. It may be thus possible for the vehicle toobtain the two-dimensional map even when communication conditions arepoor. Alternatively, the vehicle can collectively obtain thetwo-dimensional map of a wide range in advance when in a section inwhich communication conditions are good. The vehicle thus may receive alayer including the two-dimensional map without receivingthree-dimensional map 711, when communication conditions are poor and itis difficult to obtain three-dimensional map 711. Note that themeta-data is small in data size, and thus the vehicle receives themeta-data without fail, regardless, for example, of communicationconditions.

Example methods of self-location estimation using the two-dimensionalmap and self-detected three-dimensional data 712 include two methodsdescribed below.

A first method is to perform matching of two-dimensional features. Morespecifically, the vehicle extracts two-dimensional features fromself-detected three-dimensional data 712 to perform matching between theextracted two-dimensional features and the two-dimensional map.

For example, the vehicle projects self-detected three-dimensional data712 onto the same plane as that of the two-dimensional map, and matchesthe resulting two-dimensional data with the two-dimensional map. Suchmatching is performed by use of features of the two-dimensional imagesextracted from the two-dimensional data and the two-dimensional map.

When three-dimensional map 711 includes a SWLD, two-dimensional featureson the same plane as that of the two-dimensional map may be stored inthree-dimensional map 711 together with three-dimensional features ofkeypoints in a three-dimensional space. For example, identificationinformation is assigned to two-dimensional features. Alternatively,two-dimensional features are stored in a layer different from the layersof the three-dimensional data and the two-dimensional map, and thevehicle obtains data of the two-dimensional features together with thetwo-dimensional map.

When the two-dimensional map shows, on the same map, information onpositions having different heights from the ground (i.e., positions thatare not on the same plane), such as a white line inside a road, aguardrail, and a building, the vehicle extracts features from data on aplurality of heights in self-detected three-dimensional data 712.

Also, information indicating a correspondence between keypoints on thetwo-dimensional map and keypoints on three-dimensional map 711 may bestored as meta-information of the map data.

A second method is to perform matching of three-dimensional features.More specifically, the vehicle obtains three-dimensional featurescorresponding to keypoints on the two-dimensional map, and matches theobtained three-dimensional features with three-dimensional features inself-detected three-dimensional data 712.

More specifically, three-dimensional features corresponding to keypointson the two-dimensional map are stored in the map data. The vehicleobtains such three-dimensional features when obtaining thetwo-dimensional map. Note that when three-dimensional map 711 includes aSWLD, information is provided that identifies those keypoints, among thekeypoints in the SWLD, that correspond to keypoints on thetwo-dimensional map. Such identification information enables the vehicleto determine three-dimensional features that should be obtained togetherwith the two-dimensional map. In this case, the representation oftwo-dimensional positions is only required, and thus the amount of datacan be reduced compared to the case of representing three-dimensionalpositions.

The use of the two-dimensional map to perform self-location estimationdecreases the accuracy of the self-location estimation compared to thecase of using three-dimensional map 711. For this reason, the vehiclejudges whether the vehicle can continue automatic operation by use ofthe location having decreased estimation accuracy, and may continueautomatic operation only when judging that the vehicle can continueautomatic operation.

Whether the vehicle can continue automatic operation is affected by anenvironment in which the vehicle is traveling such as whether the roadon which the vehicle is traveling is a road in an urban area or a roadaccessed less often by another vehicle or a pedestrian, such as anexpressway, and the width of a road or the degree of congestion of aroad (the density of vehicles or pedestrians). It is also possible todispose, in a premise of a business place, a town, or inside a building,markers recognized by a senor such as a camera. Since a two-dimensionalsensor is capable of highly accurate recognition of such markers in thespecified areas, highly accurate self-location estimation is enabled by,for example, incorporating information on the positions of the markersinto the two-dimensional map.

Also, by incorporating, into the map, identification informationindicating whether each area corresponds to a specified area, forexample, the vehicle can judge whether such vehicle is currently in aspecified area. When in a specified area, the vehicle judges that thevehicle can continue automatic operation. As described above, thevehicle may judge whether the vehicle can continue automatic operationon the basis of the accuracy of self-location estimation that uses thetwo-dimensional map or an environment in which the vehicle is traveling.

As described above, three-dimensional information processing device 700judges whether to perform automatic operation that utilizes the locationof the vehicle having been estimated by use of the two-dimensional mapand self-detected three-dimensional data 712, on the basis of anenvironment in which the vehicle is traveling (a traveling environmentof the mobile object).

Alternatively, the vehicle may not judge whether the vehicle cancontinue automatic operation, but may switch levels (modes) of automaticoperation in accordance with the accuracy of self-location estimation orthe traveling environment of the vehicle. Here, to switch levels (modes)of automatic operation means, for example, to limit the speed, increasethe degree of driver operation (lower the automatic level of automaticoperation), switch to a mode in which the vehicle obtains information onthe operation of a preceding vehicle to refer to it for its ownoperation, switch to a mode in which the vehicle obtains information onthe operation of a vehicle heading for the same destination to use itfor automatic operation, etc.

The map may also include information, associated with the positioninformation, indicating a recommendation level of automatic operationfor the case where the two-dimensional map is used for self-locationestimation. The recommendation level may be meta-data that dynamicallychanges in accordance with the volume of traffic, etc. This enables thevehicle to determine a level only by obtaining information from the mapwithout needing to judge a level every time an environment, etc. aroundthe vehicle changes. Also, it is possible to maintain a constant levelof automatic operation of individual vehicles by such plurality ofvehicles referring to the same map. Note that the recommendation levelmay not be “recommendation,” and thus such level may be a mandatorylevel that should be abided by.

The vehicle may also switch the level of automatic operation inaccordance with the presence or absence of the driver (whether thevehicle is manned or unmanned). For example, the vehicle lowers thelevel of automatic operation when the vehicle is manned, and terminatesautomatic operation when unmanned. The vehicle may recognize apedestrian, a vehicle, and a traffic sign around the vehicle todetermine a position where the vehicle can stop safely. Alternatively,the map may include position information indicating positions where thevehicle can stop safely, and the vehicle refers to such positioninformation to determine a position where the vehicle can stop safely.

The following describes coping operations to cope with the abnormal case2 in which three-dimensional map 711 is not present, orthree-dimensional map 711 having been obtained is corrupt.

Abnormal case judgment unit 703 checks whether the current conditionapplies to one of; (1) three-dimensional map 711 of part or the entiretyof the section on the route to the destination not being present in adistribution server, etc. to which the vehicle accesses, and thusunobtainable; and (2) part or the entirety of obtained three-dimensionalmap 711 being corrupt. When one of these cases applies, the vehiclejudges that the current condition applies to the abnormal case 2. Stateddifferently, abnormal case judgment unit 703 judges whether the data ofthree-dimensional map 711 has integrity, and judges thatthree-dimensional map 711 is abnormal when the data of three-dimensionalmap 711 has no integrity.

When the current condition is judged to apply to the abnormal case 2,coping operations described below are performed. First, an examplecoping operation for the case where (1) three-dimensional map 711 isunobtainable will be described.

For example, the vehicle sets a route that avoids a section,three-dimensional map 711 of which is not present.

When being unable to set an alternative route for a reason that analternative route is not present, an alternative route is present butits distance is substantially longer, or etc., the vehicle sets a routethat includes a section, three-dimensional map 711 of which is notpresent. When in such section, the vehicle notifies the driver of thenecessity to switch to another operation mode, and switches theoperation mode to the manual mode.

When the current condition applies to (2) in which part or the entiretyof obtained three-dimensional map 711 is corrupt, a coping operationdescribed below is performed.

The vehicle identifies a corrupted portion of three-dimensional map 711,requests for the data of such corrupted portion via communication,obtains the data of the corrupted portion, and updates three-dimensionalmap 711 using the obtained data. In so doing, the vehicle may specifythe corrupted portion on the basis of position information inthree-dimensional map 711, such as absolute coordinates and relativecoordinates, or may specify the corrupted portion by an index number,etc. assigned to a random access unit that forms the corrupted portion.In such case, the vehicle replaces the random access unit including thecorrupted portion with a random access unit having been obtained.

The following describes coping operations to cope with the abnormal case3 in which the vehicle fails to generate self-detected three-dimensionaldata 712 due to trouble of a sensor of the own vehicle or bad weather.

Abnormal case judgment unit 703 checks whether an error in generatedself-detected three-dimensional data 712 falls within an acceptablerange, and judges that the current condition applies to the abnormalcase 3 when such error is beyond the acceptable range. Stateddifferently, abnormal case judgment unit 703 judges whether the dataaccuracy of generated self-detected three-dimensional data 712 is higherthan or equal to the reference value, and judges that self-detectedthree-dimensional data 712 is abnormal when the data accuracy ofgenerated self-detected three-dimensional data 712 is not higher than orequal to the reference value.

A method described below is used to check whether an error in generatedself-detected three-dimensional data 712 is within the acceptable range.

A spatial resolution of self-detected three-dimensional data 712 whenthe own vehicle is in normal operation is determined in advance on thebasis of the resolutions in the depth and scanning directions of athree-dimensional sensor of the own vehicle, such as a rangefinder and astereo camera, or on the basis of the density of generatable pointgroups. Also, the vehicle obtains the spatial resolution ofthree-dimensional map 711 from meta-information, etc. included inthree-dimensional map 711.

The vehicle uses the spatial resolutions of self-detectedthree-dimensional data 712 and three-dimensional map 711 to estimate areference value used to specify a matching error in matchingself-detected three-dimensional data 712 with three-dimensional map 711on the basis of three-dimensional features, etc. Used as the matchingerror is an error in three-dimensional features of the respectivekeypoints, statistics such as the mean value of errors inthree-dimensional features among a plurality of keypoints, or an errorin spatial distances among a plurality of keypoints. The acceptablerange of a deviation from the reference value is set in advance.

The vehicle judges that the current condition applies to the abnormalcase 3 when the matching error between self-detected three-dimensionaldata 712 generated before or in the middle of traveling andthree-dimensional map 711 is beyond the acceptable range.

Alternatively, the vehicle may use a test pattern having a knownthree-dimensional shape for accuracy check to obtain, before the startof traveling, for example, self-detected three-dimensional data 712corresponding to such test pattern, and judge whether the currentcondition applies to the abnormal case 3 on the basis of whether a shapeerror is within the acceptable range.

For example, the vehicle makes the above judgment before every start oftraveling. Alternatively, the vehicle makes the above judgment at aconstant time interval while traveling, thereby obtaining time-seriesvariations in the matching error. When the matching error shows anincreasing trend, the vehicle may judge that the current conditionapplies to the abnormal case 3 even when the error is within theacceptable range. Also, when an abnormality can be predicted on thebasis of the time-series variations, the vehicle may notify the user ofthat an abnormality is predicted by displaying, for example, a messagethat prompts the user for inspection or repair. The vehicle maydiscriminate between an abnormality attributable to a transient factorsuch as bad weather and an abnormality attributable to sensor trouble onthe basis of time-series variations, and notify the user only of anabnormality attributable to sensor trouble.

When the current condition is judged to be the abnormal case 3, thevehicle performs one, or selective ones of the following three types ofcoping operations: (1) operate an alternative emergency sensor (rescuemode); (2) switch to another operation mode; and (3) calibrate theoperation of a three-dimensional sensor.

First, the coping operation (1) operate an alternative emergency sensorwill be described. The vehicle operates an alternative emergency sensorthat is different from a three-dimensional sensor used for normaloperation. Stated differently, when the accuracy of generatedself-detected three-dimensional data 712 is not higher than or equal tothe reference value, three-dimensional information processing device 700generates self-detected three-dimensional data 712 (fourththree-dimensional position information) from information detected by thealternative sensor that is different from a usual sensor.

More specifically, when obtaining self-detected three-dimensional data712 in a combined use of a plurality of cameras or LiDARs, the vehicleidentifies a malfunctioning sensor, on the basis of a direction, etc. inwhich the matching error of self-detected three-dimensional data 712 isbeyond the acceptable range. Subsequently, the vehicle operates analternative sensor corresponding to such malfunctioning sensor.

The alternative sensor may be a three-dimensional sensor, a cameracapable of obtaining two-dimensional images, or a one-dimensional sensorsuch as an ultrasonic sensor. The use of an alternative sensor otherthan a three-dimensional sensor can result in a decrease in the accuracyof self-location estimation or the failure to perform self-locationestimation. The vehicle thus may switch automatic operation modesdepending on the type of an alternative sensor.

When an alternative sensor is a three-dimensional sensor, for example,the vehicle maintains the current automatic operation mode. When analternative sensor is a two-dimensional sensor, the vehicle switches theoperation mode from the full automatic operation mode to thesemi-automatic operation mode that requires human operation. When analternative sensor is a one-dimensional sensor, the vehicle switches theoperation mode to the manual mode that performs no automatic brakingcontrol.

Alternatively, the vehicle may switch automatic operation modes on thebasis of a traveling environment. When an alternative sensor is atwo-dimensional sensor, for example, the vehicle maintains the fullautomatic operation mode when traveling on an expressway, and switchesthe operation mode to the semi-automatic operation mode when travelingin an urban area.

Also, even when no alternative sensor is available, the vehicle maycontinue the self-location estimation so long as a sufficient number ofkeypoints are obtainable only by normally operating sensors. Sincedetection cannot work in a specific direction in this case, the vehicleswitches the current operation mode to the semi-automatic operation modeor the manual mode.

Next, the coping operation (2) switch to another operation mode will bedescribed. The vehicle switches the current operation mode from theautomatic operation mode to the manual mode. The vehicle may continueautomatic operation until arriving at the shoulder of the road, oranother place where the vehicle can stop safely, and then stop there.The vehicle may switch the current operation mode to the manual modeafter stopping. As described above, three-dimensional informationprocessing device 700 switches the automatic operation mode to anothermode when the accuracy of generated self-detected three-dimensional data712 is not higher than or equal to the reference value.

Next, the coping operation (3) calibrate the operation of athree-dimensional sensor will be described. The vehicle identifies amalfunctioning three-dimensional sensor from a direction, etc. in whichan matching error is occurring, and calibrates the identified sensor.More specifically, when a plurality of LiDARs or cameras are used assensors, an overlapped portion is included in a three-dimensional spacereconstructed by each of the sensors. Stated differently, datacorresponding to such overlapped portion is obtained by a plurality ofsensors. However, a properly operating sensor and a malfunctioningsensor obtain different three-dimensional point group data correspondingto the overlapped portion. The vehicle thus calibrates the origin pointof the LiDAR or adjusts the operation for a predetermined part such asone responsible for camera exposure and focus so that the malfunctioningsensor can obtain the data of a three-dimensional point group equivalentto that obtained by a properly operating sensor.

When the matching error falls within the acceptable range as a result ofsuch adjustment, the vehicle maintains the previous operation mode.Meanwhile, when the matching accuracy fails to fall within theacceptable range after such adjustment, the vehicle performs one of theabove coping operations: (1) operate an alternative emergency sensor;and (2) switch to another operation mode.

As described above, three-dimensional information processing device 700calibrates a sensor operation when the data accuracy of generatedself-detected three-dimensional data 712 is not higher than or equal tothe reference value.

The following describes a method of selecting a cooping operation. Acoping operation may be selected by the user such as a driver, or may beautomatically selected by the vehicle without user's involvement.

The vehicle may switch controls in accordance with whether the driver isonboard. For example, when the driver is onboard, the vehicleprioritizes the manual mode. Meanwhile, when the driver is not onboard,the vehicle prioritizes the mode to move to a safe place and stop.

Three-dimensional map 711 may include information indicating places tostop as meta-information. Alternatively, the vehicle may issue, to aservice firm that manages operation information on a self-drivingvehicle, a request to send a reply indicating a place to stop, therebyobtaining information on the place to stop.

Also, when the vehicle travels on a fixed route, for example, theoperation mode of the vehicle may be switched to a mode in which anoperator controls the operation of the vehicle via a communicationchannel. It is highly dangerous when there is a failure in the functionof self-location estimation especially when the vehicle is traveling inthe full automatic operation mode. When any abnormal case is detected ora detected abnormality cannot be fixed, the vehicle notifies, via acommunication channel, the service firm that manages the operationinformation of the occurrence of the abnormality. Such service firm maynotify vehicles, etc. traveling around such vehicle in trouble of thepresence of a vehicle having an abnormality or that they should clear anearby space for the vehicle to stop.

The vehicle may also travel at a decreased speed compared to normaltimes when any abnormal case has been detected.

When the vehicle is a self-driving vehicle from a vehicle dispatchservice such as a taxi, and an abnormal case occurs in such vehicle, thevehicle contacts an operation control center, and then stops at a safeplace. The firm of the vehicle dispatch service dispatches analternative vehicle. The user of such vehicle dispatch service mayoperate the vehicle instead. In these cases, fee discount or benefitpoints may be provided in combination.

In the description of the coping operations for the abnormal case 1,self-location estimation is performed on the basis of thetwo-dimensional map, but self-location estimation may be performed alsoin normal times by use of the two-dimensional map. FIG. 36 is aflowchart of self-location estimation processes performed in such case.

First, the vehicle obtains three-dimensional map 711 of the surroundingsof the traveling route (S711). The vehicle then obtains self-detectedthree-dimensional data 712 on the basis of sensor information (S712).

Next, the vehicle judges whether three-dimensional map 711 is necessaryfor self-location estimation (S713). More specifically, the vehiclejudges whether three-dimensional map 711 is necessary on the basis ofthe accuracy of its location having been estimated by use of thetwo-dimensional map and the traveling environment. For example, a methodsimilar to the above-described coping operations for the abnormal case 1is used.

When judging that three-dimensional map 711 is not necessary (No inS714), the vehicle obtains a two-dimensional map (S715). In so doing,the vehicle may obtain additional information together that is mentionedwhen the coping operations for the abnormal case 1 have been described.Alternatively, the vehicle may generate a two-dimensional map fromthree-dimensional map 711. For example, the vehicle may generate atwo-dimensional map by cutting out any plane from three-dimensional map711.

Next, the vehicle performs self-location estimation by use ofself-detected three-dimensional data 712 and the two-dimensional map(S716). Note that a method of self-location estimation by use of atwo-dimensional map is similar to the above-described coping operationsfor the abnormal case 1.

Meanwhile, when judging that three-dimensional map 711 is necessary (Yesin S714), the vehicle obtains three-dimensional map 711 (S717). Then,the vehicle performs self-location estimation by use of self-detectedthree-dimensional data 712 and three-dimensional map 711 (S718).

Note that the vehicle may selectively decide on which one of thetwo-dimensional map and three-dimensional map 711 to basically use, inaccordance with a speed supported by a communication device of the ownvehicle or conditions of a communication channel. For example, acommunication speed that is required to travel while receivingthree-dimensional map 711 is set in advance, and the vehicle maybasically use the two-dimensional map when the communication speed atthe time of traveling is less than or equal to the such set value, andbasically use three-dimensional map 711 when the communication speed atthe time of traveling is greater than the set value. Note that thevehicle may basically use the two-dimensional map without judging whichone of the two-dimensional map and the three-dimensional map to use.

Although the three-dimensional information processing device accordingto the embodiments of the present disclosure has been described above,the present disclosure is not limited to such embodiments.

Note that each of the processing units included in the three-dimensionalinformation processing device according to the embodiments isimplemented typically as a large-scale integration (LSI), which is anintegrated circuit (IC). They may take the form of individual chips, orone or more or all of them may be encapsulated into a single chip.

Such IC is not limited to an LSI, and thus may be implemented as adedicated circuit or a general-purpose processor. Alternatively, a fieldprogrammable gate array (FPGA) that allows for programming after themanufacture of an LSI, or a reconfigurable processor that allows forreconfiguration of the connection and the setting of circuit cellsinside an LSI may be employed.

Moreover, in the above embodiments, the structural components may beimplemented as dedicated hardware or may be realized by executing asoftware program suited to such structural components. Alternatively,the structural components may be implemented by a program executor suchas a CPU or a processor reading out and executing the software programrecorded in a recording medium such as a hard disk or a semiconductormemory.

Also, the present disclosure may be embodied as a three-dimensionalinformation processing method performed by the three-dimensionalinformation processing device.

Also, the divisions of the functional blocks shown in the block diagramsare mere examples, and thus a plurality of functional blocks may beimplemented as a single functional block, or a single functional blockmay be divided into a plurality of functional blocks, or one or morefunctions may be moved to another functional block. Also, the functionsof a plurality of functional blocks having similar functions may beprocessed by single hardware or software in a parallelized ortime-divided manner.

Also, the processing order of executing the steps shown in theflowcharts is a mere illustration for specifically describing thepresent disclosure, and thus may be an order other than the shown order.Also, one or more of the steps may be executed simultaneously (inparallel) with another step.

Although the three-dimensional information processing device accordingto one or more aspects has been described on the basis of theembodiments, the present disclosure is not limited to such embodiments.The one or more aspects may thus include an embodiment achieved bymaking various modifications to the above embodiments that can beconceived by those skilled in the art as well as an embodiment achievedby combining structural components in different embodiments, withoutmaterially departing from the spirit of the present disclosure.

Embodiment 5

Other application examples of the configurations of the image processingmethod and apparatus described in each embodiment described above and asystem using the application examples will be described. The system isapplicable to an increasingly intelligent video system with object spaceextending to a wider area. For example, the system is applicable to (1)a monitoring system mounted in a security camera of a store or afactory, a vehicle-mounted camera of the police or the like, (2) atransportation information system using a camera owned by an individualperson, each vehicle-mounted camera, a camera installed in a road or thelike, (3) an environmental research or delivery system using aremote-controllable or auto-controllable apparatus such as a drone, and(4) a content transmission and reception system of a video or the likeusing a camera installed in an entertainment facility, a stadium or thelike, a moving camera such as a drone, a camera owned by an individualperson or the like.

FIG. 37 is a diagram illustrating a configuration of video informationprocessing system ex100 according to the present embodiment. The presentembodiment describes an example of preventing occurrence of a blind spotand an example of prohibiting capturing of a specific area.

Video information processing system ex100 illustrated in FIG. 37includes video information processing apparatus ex101, a plurality ofcameras ex102, and video reception apparatus ex103. Note that videoinformation processing system ex100 does not necessarily need to includevideo reception apparatus ex103.

Video information processing apparatus ex101 includes storage ex111 andanalyzer ex112. Each of N cameras ex102 has a function of capturingvideos and a function of transmitting captured video data to videoinformation processing apparatus ex101. Moreover, camera ex102 may havea function of displaying a video that is being captured. Note thatcamera ex102 may code a captured video signal by using a coding schemesuch as HEVC or H.264, and may then transmit the coded video signal tovideo information processing apparatus ex101, or camera ex102 maytransmit the video data that is not coded to video informationprocessing apparatus ex101.

Here, each camera ex102 is a fixed camera such as a monitoring camera, amoving camera mounted in a radio-controlled unmanned flight vehicle, avehicle or the like, or a user camera owned by a user.

The moving camera receives an instruction signal transmitted from videoinformation processing apparatus ex101, and changes a position orcapturing direction of the moving camera itself in response to thereceived instruction signal.

Moreover, time of the plurality of cameras ex102 is calibrated by usingtime information of a server or a reference camera prior to start ofcapturing. Moreover, spatial positions of the plurality of cameras ex102are calibrated based on how an object in space to be captured iscaptured or a relative position from a reference camera.

Storage ex111 in information processing apparatus ex101 stores the videodata transmitted from N cameras ex102.

Analyzer ex112 detects a blind spot from the video data stored instorage ex111, and transmits to the moving camera the instruction signalthat indicates an instruction to the moving camera for preventingoccurrence of a blind spot. The moving camera moves in response to theinstruction signal, and continues capturing.

Analyzer ex112 detects a blind spot by using Structure from Motion(SfM), for example. SfM is a technique of restoring a three-dimensionalshape of a subject from a plurality of videos captured from differentpositions, and SfM is widely known as a shape restoration technology ofestimating a subject shape and a camera position simultaneously. Forexample, analyzer ex112 restores the three-dimensional shape in thefacility or in the stadium from the video data stored in storage ex111by using SfM, and detects as a blind spot an area that cannot berestored.

Note that when the position and capturing direction of camera ex102 arefixed and information of the position and capturing direction is known,analyzer ex112 may perform SfM by using these pieces of knowninformation. Moreover, when the position and capturing direction of themoving camera can be acquired with, for example, a GPS and angle sensorin the moving camera, the moving camera may transmit information of theposition and capturing direction of the moving camera to analyzer ex112,and analyzer ex112 may perform SfM by using the transmitted informationof the position and the capturing direction.

Note that a method for detecting a blind spot is not limited to theabove-described method using SfM. For example, analyzer ex112 may useinformation from a depth sensor such as a laser range finder, to know aspatial distance of the object to be captured. Moreover, when an imageincludes a marker that is set in space in advance or a specific object,analyzer ex112 may detect information of the camera position, capturingdirection, and zoom magnification from the size of the marker or theobject. Thus, analyzer ex112 detects a blind spot by using any methodthat enables detection of the capturing area of each camera. Moreover,analyzer ex112 may acquire, for example, information of a mutualpositional relationship between a plurality of objects to be captured,from video data or a proximity sensor, and analyzer ex112 may identifyan area where a blind spot is highly likely to occur, based on theacquired positional relationship.

Here, the blind spot includes not only a portion having no video in anarea to be captured but also a portion having poor image quality ascompared to other portions, and a portion having no predetermined imagequality. This portion to be detected may be set appropriately accordingto the configuration or purpose of the system. For example, requiredimage quality of a specific subject in space to be captured may be sethigh. Moreover, conversely, the required image quality of a specificarea in space to be captured may be set low, and the required imagequality may be set such that the area is not determined to be a blindspot even when no video is captured.

Note that the above-described image quality includes various pieces ofinformation regarding a video, such as area occupied by a subject to becaptured in the video (for example, a number of pixels), or whether thevideo is focused on the subject to be captured. Based on these pieces ofinformation or combination thereof, whether the area is a blind spot maybe determined.

Note that detection of the area that is actually a blind spot isdescribed above, but the area that needs to be detected in order toprevent occurrence of a blind spot is not limited to the area that isactually a blind spot. For example, when a plurality of objects to becaptured exists and at least part of the objects is moving, a new blindspot is likely to occur because another object to be captured entersbetween a certain object to be captured and a camera. Meanwhile,analyzer ex112 may detect movement of the plurality of objects to becaptured from, for example, the captured video data, and analyzer ex112may estimate the area that is likely to become a new blind spot, basedon the detected movement of the plurality of objects to be captured andpositional information of camera ex102. In this case, video informationprocessing apparatus ex101 may transmit the instruction signal to themoving camera to capture the area that is likely to become a blind spot,and video information processing apparatus ex101 may prevent occurrenceof a blind spot.

Note that when there is a plurality of moving cameras, video informationprocessing apparatus ex101 needs to select any of the moving cameras towhich the instruction signal is to be transmitted in order to cause themoving camera to capture a blind spot or an area that is likely tobecome a blind spot. Moreover, when there is a plurality of movingcameras and there is a plurality of blind spots or areas that are likelyto become blind spots, video information processing apparatus ex101needs to determine which blind spot or area that is likely to become ablind spot each of the plurality of moving cameras is to capture. Forexample, video information processing apparatus ex101 selects the movingcamera closest to a blind spot or an area that is likely to become ablind spot, based on a position of a blind spot or an area that islikely to become a blind spot, and a position of an area each movingcamera is capturing. Moreover, video information processing apparatusex101 may determine for each camera whether a new blind spot occurs whenvideo data which the moving camera is currently capturing is notobtained, and video information processing apparatus ex101 may selectthe moving camera that is determined that a blind spot does not occureven when the video data which is currently being captured is notobtained.

The above-described configuration enables video information processingapparatus ex101 to prevent occurrence of a blind spot by detecting ablind spot and transmitting the instruction signal to the moving cameraso as to prevent the blind spot.

Variation 1

Note that the example of transmitting the instruction signal forinstructing the moving camera to move is described above; however, theinstruction signal may be a signal for instructing the user of the usercamera to move. For example, the user camera displays an instructionimage that instructs the user to change the direction of the camera,based on the instruction signal. Note that the user camera may displaythe instruction image that indicates a movement path on a map, as theuser movement instruction. Moreover, in order to improve the quality ofthe acquired image, the user camera may display detailed capturinginstructions such as the capturing direction, an angle, an angle ofview, image quality, and movement of the capturing area. Further, videoinformation processing apparatus ex101 may automatically control suchfeature data of camera ex102 regarding capturing when the feature datais controllable on a video information processing apparatus ex101 side.

Here, the user camera is, for example, a smartphone, a tablet terminal,a wearable terminal, or a head mounted display (HMD) that a spectator inthe stadium or a guard in the facility carries.

Moreover, a display terminal that displays the instruction image doesnot need to be identical to the user camera that captures video data.For example, the user camera may transmit the instruction signal or theinstruction image to the display terminal associated with the usercamera in advance, and the display terminal may display the instructionimage. Moreover, information of the display terminal corresponding tothe user camera may be registered in video information processingapparatus ex101 in advance. In this case, video information processingapparatus ex101 may cause the display terminal to display theinstruction image by transmitting the instruction signal directly to thedisplay terminal corresponding to the user camera.

Variation 2

Analyzer ex112 may generate a free viewpoint video (three-dimensionalreconfiguration data), for example, by using SfM to restore thethree-dimensional shape in the facility or in the stadium from the videodata stored in storage ex111. This free viewpoint video is stored instorage ex111. Video information processing apparatus ex101 reads fromstorage ex111 the video data according to visual field information(and/or viewpoint information) transmitted from video receptionapparatus ex103, and transmits the read video data to video receptionapparatus ex103. Note that video reception apparatus ex103 may be one ofthe plurality of cameras.

Variation 3

Video information processing apparatus ex101 may detect a capturingprohibited area. In this case, analyzer ex112 analyzes the capturedimage, and when the moving camera is capturing the capturing prohibitedarea, analyzer ex112 transmits a capturing prohibition signal to themoving camera. The moving camera stops capturing while receiving thecapturing prohibition signal.

For example, analyzer ex112 matches three-dimensional virtual spacerestored by using SfM with the captured video, and accordingly analyzerex112 determines whether the moving camera set in advance in space iscapturing the capturing prohibited area. Alternatively, analyzer ex112determines whether the moving camera is capturing the capturingprohibited area, by using a marker or characteristic object placed inspace as a trigger. The capturing prohibited area is, for example, arest room in the facility or in the stadium.

Moreover, when the user camera is capturing the capturing prohibitedarea, the user camera may notify the user of a fact that the currentplace is a capturing prohibited place, by causing a display connectedwirelessly or with wires to display a message, or by outputting a soundor voice from a speaker or an earphone.

For example, a fact that capturing in the current direction of thecamera orientation is prohibited is displayed as the message.Alternatively, the capturing prohibited area and the current capturingarea are indicated on a displayed map. Moreover, the capturing isautomatically resumed, for example, when the capturing prohibitionsignal is no longer output. Moreover, the capturing may be resumed whenthe capturing prohibition signal is not output and the user performsoperations for resuming the capturing. Moreover, when the capturing isstopped and resumed twice or more in a short period, calibration may beperformed again. Moreover, notification for checking the currentposition or for prompting movement may be given to the user.

Moreover, in a case of special work such as the police, pass code orfingerprint authentication or the like that disables such a function maybe used for recording. Further, even in such a case, when the video ofthe capturing prohibited area is displayed or stored outside, imageprocessing such as mosaic may be performed automatically.

The above configuration enables video information processing apparatusex101 to set a certain area as the capturing prohibited area byperforming determination of capturing prohibition and giving the usernotification for stopping capturing.

Variation 4

Since it is necessary to collect videos of the plurality of viewpointsin order to construct three-dimensional virtual space from the videos,video information processing system ex100 sets an incentive for a userwho transmits a captured video. For example, video informationprocessing apparatus ex101 distributes videos with no charge or atdiscount rate to the user that transmits a video, or gives the user whotransmits a video a point having a monetary value that can be used in anonline or off-line store or in a game, or a point having a non-monetaryvalue such as a social status in virtual space such as a game. Moreover,video information processing apparatus ex101 gives a particularly highpoint to the user who transmits the captured video of a valuable visualfield (and/or viewpoint) such as a frequently requested video.

Variation 5

Video information processing apparatus ex101 may transmit additionalinformation to the user camera based on an analysis result made byanalyzer ex112. In this case, the user camera superimposes theadditional information of the captured video, and displays thesuperimposed video on a screen. The additional information is, forexample, information of a player such as a player name or height when agame in a stadium is captured, and the player name or a photograph ofthe player's face is displayed in association with each player in thevideo. Note that video information processing apparatus ex101 mayextract the additional information by search via the Internet based onpart or all areas of the video data. Moreover, camera ex102 may receivesuch additional information by the near field communication includingBluetooth (registered trademark) or by visible light communication fromillumination of the stadium or the like, and may map the receivedadditional information to the video data. Moreover, camera ex102 mayperform this mapping based on a certain rule such as a table that iskept in the storage connected to camera ex102 wirelessly or with wiresand that indicates correspondence between the information obtained bythe visible light communication technology and the additionalinformation. Camera ex102 may perform this mapping by using a result ofa most probable combination by Internet search.

Moreover, in the monitoring system, a highly accurate monitoring systemcan be implemented, for example, by superimposition of information of aperson on a blacklist on the user camera carried by a guard in thefacility.

Variation 6

Analyzer ex112 may determine which area in the facility or in thestadium the user camera is capturing, by matching the free viewpointvideo with the video captured by the user camera. Note that the methodfor determining the capturing area is not limited thereto, but variousmethods for determining the capturing area described in each of theabove-described embodiments or other methods for determining thecapturing area may be used.

Video information processing apparatus ex101 transmits a past video tothe user camera based on the analysis result made by analyzer ex112. Theuser camera superimposes the past video on the captured video, orreplaces the captured video with the past video, and displays the videoon a screen.

For example, a highlight scene of a first half is displayed as a pastvideo during halftime. This enables the user to enjoy the highlightscene of the first half during halftime as a video captured in adirection in which the user is watching. Note that the past video is notlimited to the highlight scene of the first half, but may be thehighlight scene of the past game held in the stadium. Moreover, timingat which video information processing apparatus ex101 distributes thepast video is not limited to timing of distributing during halftime, butmay be, for example, timing of distributing after the game end or duringthe game. In particular, in the case of distributing during halftime,video information processing apparatus ex101 may distribute a scenewhich the user has missed and which is considered to be important, basedon the analysis result made by analyzer ex112. Moreover, videoinformation processing apparatus ex101 may distribute the past videoonly when there is a user request, or may distribute a message ofdistribution permission prior to distribution of the past video.

Variation 7

Video information processing apparatus ex101 may transmit advertisementinformation to the user camera based on the analysis result made byanalyzer ex112. The user camera superimposes the advertisementinformation of the captured video, and displays the superimposed videoon a screen.

The advertisement information may be distributed, for example,immediately before distribution of the past video during halftime orafter the game end as described in variation 6. This enables adistribution company to obtain advertising rates from an advertiser andto provide the user with video distribution services at a low cost orwith no charge. Moreover, video information processing apparatus ex101may distribute a message of advertisement distribution permissionimmediately before distribution of the advertisement information, or mayprovide services with no charge only when the user views theadvertisement, or may provide services at a lower cost than a cost inthe case where the user does not view the advertisement.

Moreover, when the user clicks “Order now” or the like in response tothe advertisement, a staff member who knows the position of the userbased on the system or some positional information, or an automaticdelivery system in the facility delivers an ordered drink to a seat ofthe user. Payment may be made by hand delivery to the staff member, ormay be made based on credit card information set in an app of a mobileterminal or the like in advance. Moreover, the advertisement may includea link to an e-commerce site, and on-line shopping such as ordinary homedelivery may be possible.

Variation 8

Video reception apparatus ex103 may be one of the cameras ex102 (usercameras). In this case, analyzer ex112 matches the free viewpoint videowith the video captured by the user camera, and accordingly analyzerex112 determines which area in the facility or in the stadium the usercamera is capturing. Note that the method for determining the capturingarea is not limited thereto.

For example, when the user performs a swipe operation in a direction ofan arrow displayed on a screen, the user camera generates viewpointinformation that indicates movement of the viewpoint in the direction.Video information processing apparatus ex101 reads from storage ex111the video data that captures an area that is moved according to theviewpoint information from the area captured by the user cameradetermined by analyzer ex112, and video information processing apparatusex101 starts transmission of the read video data to the user camera.Then, the user camera displays the video distributed from videoinformation processing apparatus ex101, instead of the captured video.

This enables the user in the facility or in the stadium to view thevideo captured from a favorite viewpoint with such a simple operation asscreen swipe. For example, a spectator who is watching a game on a thirdbase side of a baseball stadium can view the video captured from theviewpoint on a first base side. Moreover, the monitoring system enablesa guard in the facility to view, for example, the video from theviewpoint from which the guard wants to check or the video to be watchedclosely as an interruption from a center, while changing the viewpointadaptively, with such a simple operation as screen swipe. For thisreason, a highly accurate monitoring system can be implemented.

Moreover, distribution of the video to the user in the facility or inthe stadium is effective, for example, even when an obstacle existsbetween the user camera and an object to be captured, and there is aninvisible area. In this case, the user camera may switch the video ofsome area of the areas captured by the user camera that includes theobstacle, from the captured video to a video distributed from videoinformation processing apparatus ex101, and may display the distributedvideo, or the user camera may switch the entire screen from the capturedvideo to the distributed video, and may display the distributed video.Moreover, the user camera may combine the captured video with thedistributed video to display the video that seems to penetrate theobstacle such that the object to be viewed is visible. Even when theobject to be captured is invisible from the position of the user due toinfluence of the obstacle, this configuration can reduce the influenceof the obstacle because the user can view the video distributed fromvideo information processing apparatus ex101.

Moreover, when the distributed video is displayed as the video of thearea invisible due to the obstacle, display switching control differentfrom display switching control depending on input processing made by theuser such as the screen swipe described above may be performed. Forexample, when it is determined that the capturing area includes theobstacle, based on information of movement and capturing direction ofthe user camera, and based on positional information of the obstacleobtained in advance, display switching from the captured video to thedistributed video may be performed automatically. Moreover, when it isdetermined from analysis of the captured video data that the obstaclewhich is not the object to be captured is being captured, displayswitching from the captured video to the distributed video may beperformed automatically. Moreover, when area of the obstacle in thecaptured video (for example, a number of pixels) exceeds a predeterminedthreshold, or when a ratio of the area of the obstacle to area of theobject to be captured exceeds a predetermined proportion, displayswitching from the captured video to the distributed video may beperformed automatically.

Note that the display switching from the captured video to thedistributed video, and display switching from the distributed video tothe captured video may performed in response to the input processingmade by the user.

Variation 9

A speed at which the video data is transmitted to video informationprocessing apparatus ex101 may be instructed based on importance of thevideo data captured by each camera ex102.

In this case, analyzer ex112 determines importance of video data storedin storage ex111 or importance of camera ex102 that captures the videodata. The determination of the importance here is made based on, forexample, a number of persons or a number of moving objects in the video,the information such as image quality of the video data, or combinationthereof.

Moreover, the determination of the importance of the video data may bemade based on the position of camera ex102 that captures the video dataor the area captured in the video data. For example, when a plurality ofother capturing cameras ex102 exists near camera ex102 concerned, theimportance of the video data captured by camera ex102 concerned is setlow. Moreover, when the position of camera ex102 concerned is distantfrom the positions of other cameras ex102, but there exists a pluralityof other cameras ex102 that captures an identical area, the importanceof the video data captured by camera ex102 concerned is set low.Moreover, the determination of the importance of the video data may bemade based on frequency of requests in video distribution services. Notethat the method for determining the importance is limited to neither theabove-described methods nor combination thereof, but may be a methodaccording to the configuration or purpose of the monitoring system orvideo distribution system.

Moreover, the determination of the importance may not be made based onthe captured video data. For example, the importance of camera ex102that transmits the video data to terminals other than video informationprocessing apparatus ex101 may be set high. Conversely, the importanceof camera ex102 that transmits the video data to terminals other thanvideo information processing apparatus ex101 may be set low.Accordingly, for example, when a plurality of services that needstransmission of video data uses a common communication band, a degree offreedom of controlling the communication band according to a purpose orcharacteristics of each service increases. This prevents quality of eachservice from degrading because necessary video data cannot be obtained.

Moreover, analyzer ex112 may determine the importance of the video databy using the free viewpoint video and the captured video of cameraex102.

Video information processing apparatus ex101 transmits a communicationspeed instruction signal to camera ex102 based on a determination resultof the importance made by analyzer ex112. Video information processingapparatus ex101 gives instruction of high speed communication to, forexample, camera ex102 that is capturing a video with high importance.Moreover, in addition to speed control, regarding important information,video information processing apparatus ex101 may transmit a signal thatinstructs a scheme for sending the important information twice or morein order to reduce disadvantages owing to loss. This enables efficientcommunication in the entire facility or in the entire stadium. Note thatcommunication between camera ex102 and video information processingapparatus ex101 may be wired communication, or may be wirelesscommunication. Moreover, video information processing apparatus ex101may control only any one of the wired communication and wirelesscommunication.

Camera ex102 transmits the captured video data to video informationprocessing apparatus ex101 at the communication speed according to thecommunication speed instruction signal. Note that when retransmissionfails predetermined number of times, camera ex102 may stopretransmission of the captured video data and start transmission of nextcaptured video data. This enables efficient communication in the entirefacility or in the entire stadium and high-speed processing in analyzerex112 can be implemented.

Moreover, when the communication speed allocated to each camera ex102fails to have a bandwidth sufficient for transmitting the captured videodata, camera ex102 may convert the captured video data into video datawith a bit rate that enables transmission at the allocated communicationspeed, and transmit the converted video data, or may stop transmissionof the video data.

Moreover, as described above, when the video data is used for preventingoccurrence of a blind spot, only some area of the capturing areas in thecaptured video data is likely to be needed for filling the blind spot.In this case, camera ex102 may generate extracted video data byextracting only at least the area needed for preventing occurrence ofthe blind spot from the video data, and transmit the generated extractedvideo data to video information processing apparatus ex101. Thisconfiguration can realize suppression of occurrence of the blind spot ata narrower communication bandwidth.

Moreover, for example, when superimposed display or video distributionof the additional information is performed, camera ex102 needs totransmit the positional information and information of the capturingdirection of camera ex102 to video information processing apparatusex101. In this case, camera ex102 to which only the bandwidthinsufficient for transmitting the video data is allocated may transmitonly the positional information and information of the capturingdirection detected by camera ex102. Moreover, when video informationprocessing apparatus ex101 estimates the positional information andinformation of the capturing direction of camera ex102, camera ex102 mayconvert the captured video data into video data with resolutionnecessary for estimation of the positional information and theinformation of the capturing direction, and transmit the converted videodata to video information processing apparatus ex101. This configurationcan also provide superimposed display or video distribution services ofthe additional information to camera ex102 to which only the narrowcommunication bandwidth is allocated. Moreover, since video informationprocessing apparatus ex101 can acquire information of the capturing areafrom more cameras ex102, video information processing apparatus ex101 iseffective, for example, for using information of the capturing area fora purpose of detecting an area that attracts attention, or the like.

Note that the above-described switching of transmission processing ofthe video data according to the allocated communication bandwidth may beperformed by camera ex102 based on the notified communication bandwidth,or video information processing apparatus ex101 may determine theoperation of each camera ex102 and notify each camera ex102 of a controlsignal that indicates the determined operation. This enables appropriatesharing of tasks of processing according to an amount of calculationnecessary for determination of switching of the operations, throughputof camera ex102, required communication bandwidth, and the like.

Variation 10

Analyzer ex112 may determine the importance of the video data based onthe visual field information (and/or viewpoint information) transmittedfrom video reception apparatus ex103. For example, analyzer ex112 setshigh importance of the captured video data including a lot of areasindicated by the visual field information (and/or viewpointinformation). Moreover, analyzer ex112 may determine the importance ofthe video data in consideration of the number of persons or the numberof moving objects in the video. Note that the method for determining theimportance is not limited thereto.

Note that a communication control method described in the presentembodiment does not necessarily need to be used in a system thatreconstructs the three-dimensional shape from the plurality of pieces ofvideo data. For example, when video data is transmitted by wiredcommunication and/or wireless communication selectively or at adifferent transmission speed in an environment where there exists aplurality of cameras ex102, the communication control method describedin the present embodiment is effective.

Variation 11

In the video distribution system, video information processing apparatusex101 may transmit an outline video that indicates an entire capturingscene to video reception apparatus ex103.

Specifically, when video information processing apparatus ex101 hasreceived a distribution request transmitted from video receptionapparatus ex103, video information processing apparatus ex101 reads theoutline video of an inside of the entire facility or an inside of theentire stadium from storage ex111, and transmits the external appearancevideo to video reception apparatus ex103. This outline video may have along update interval (may have a low frame rate), and may have low imagequality. A viewer touches a portion to watch in the outline videodisplayed on a screen of video reception apparatus ex103. Accordingly,video reception apparatus ex103 transmits the visual field information(and/or viewpoint information) corresponding to the touched portion tovideo information processing apparatus ex101.

Video information processing apparatus ex101 reads the video datacorresponding to the visual field information (and/or viewpointinformation) from storage ex111, and transmits the video data to videoreception apparatus ex103.

Moreover, analyzer ex112 generates the free viewpoint video bypreferentially restoring the three-dimensional shape (three-dimensionalreconfiguration) of the area indicated by the visual field information(and/or viewpoint information). Analyzer ex112 restores thethree-dimensional shape of an inside of the entire facility or an insideof the entire stadium with accuracy in the extent of indicating theoutline. Accordingly, video information processing apparatus ex101 canefficiently restore the three-dimensional shape. As a result, a highframe rate and high image quality of the free viewpoint video of thearea the viewer wants to watch can be implemented.

Variation 12

Note that video information processing apparatus ex101 may store inadvance as a previous video, for example, three-dimensional shaperestored data of the facility or stadium generated in advance fromdesign drawings or the like. Note that the previous video is not limitedthereto, but may be virtual space data in which unevenness of spaceobtained from a depth sensor and a picture derived from a past image orvideo data or an image or video data at a time of calibration are mappedfor each object.

For example, when soccer is played in a stadium, analyzer ex112 mayrestore the three-dimensional shapes of only players and a ball, andgenerate the free viewpoint video by combining the obtained restoreddata and the previous video. Alternatively, analyzer ex112 maypreferentially restore the three-dimensional shapes of players and aball. Accordingly, video information processing apparatus ex101 canrestore the three-dimensional shape efficiently. As a result, a highframe rate and high image quality of the free viewpoint video regardingplayers and a ball to which viewers pay attention can be implemented.Moreover, in the monitoring system, analyzer ex112 may preferentiallyrestore the three-dimensional shapes of only persons and moving objects.

Variation 13

Time of each apparatus may be calibrated when capturing starts, based oninformation such as reference time of the server. Analyzer ex112restores the three-dimensional shape by using the plurality of pieces ofvideo data captured at time within a preset time range among theplurality of pieces of captured video data captured by the plurality ofcameras ex102 in accordance with accuracy of time settings. Thisdetection of time uses, for example, time when the captured video datais stored in storage ex111. Note that the method for detecting time isnot limited thereto. Accordingly, since video information processingapparatus ex101 can restore the three-dimensional shape efficiently, ahigh frame rate and high image quality of the free viewpoint video canbe implemented.

Alternatively, analyzer ex112 may restore the three-dimensional shape byusing only high-quality data, or by preferentially using high-qualitydata among the plurality of pieces of video data stored in storageex111.

Variation 14

Analyzer ex112 may restore the three-dimensional shape by using cameraattribute information. For example, analyzer ex112 may generate thethree-dimensional shape video by a method such as a volume intersectiontechnique or a multi-view stereo method by using camera attributeinformation. In this case, camera ex102 transmits the captured videodata and the camera attribute information to video informationprocessing apparatus ex101. Examples of the camera attribute informationinclude a capturing position, a capturing angle, capturing time, andzoom magnification.

Accordingly, since video information processing apparatus ex101 canrestore the three-dimensional shape efficiently, a high frame rate andhigh image quality of the free viewpoint video can be implemented.

Specifically, camera ex102 defines three-dimensional coordinates in thefacility or in the stadium, and transmits to video informationprocessing apparatus ex101 information as camera attribute informationthat indicates an angle, zoom magnification, and time of capturing ofcertain coordinates by camera ex102, together with the video. Moreover,when camera ex102 is activated, a clock on a communication network inthe facility or in the stadium is synchronized with a clock in thecamera, and time information is generated.

Moreover, the positional and angle information of camera ex102 isacquired by pointing camera ex102 at a specific point in the facility orin the stadium when camera ex102 is activated or at any timing. FIG. 38is a diagram illustrating an example of notification displayed on ascreen of camera ex102 when camera ex102 is activated. When the usermatches “+” displayed in a center of the screen with “+” which is in acenter of a soccer ball in advertisement in north of the stadium inresponse to this notification and touches the display of camera ex102,camera ex102 acquires vector information from camera ex102 to theadvertisement, and identifies reference of the camera position andangle. Subsequently, camera coordinates and an angle at each time areidentified from motion information of camera ex102. Of course, thedisplay is not limited thereto, and display that instructs coordinates,an angle, or a movement speed of the capturing area during a capturingperiod by using an arrow or the like may be used.

The coordinates of camera ex102 may be identified by using a radio waveof the global positioning system (GPS), wireless fidelity (WiFi)(registered trademark), third generation (3G), long term evolution(LTE), and fifth generation (5G) (wireless LAN), or by using the nearfield communication such as beacon (Bluetooth (registered trademark),ultrasonic waves). Moreover, information about which base station in thefacility or in the stadium has received the captured video data may beused.

Variation 15

The system may be provided as an application that operates on a mobileterminal such as a smartphone.

Accounts of various social networking services (SNS) or the like may beused for login to the system. Note that an account dedicated to an appor a guest account that has limited functions may be used. Favoritevideos, favorite accounts or the like can be evaluated by using theaccounts in such a manner. Moreover, the bandwidth is preferentiallyallocated to, for example, video data similar to video data that isbeing captured or viewed, or to video data of the viewpoint similar tothe viewpoint of video data that is being captured or viewed, and thiscan increase resolution of these pieces of video data. Accordingly, thethree-dimensional shape from these viewpoints can be restored withbetter accuracy.

Moreover, the user can preferentially watch the selected image overother users by selecting a favorite image video and by following theother party with the application, or the user can have connection bytext chatting or the like on condition of approval of the other party.Thus, it is possible to generate a new community.

Thus, connection between the users in the community can activatecapturing itself or sharing of captured images, and can promptrestoration of three-dimensional shapes with higher accuracy.

Moreover, according to settings of connection in the community, the usercan edit images or videos captured by another person, or can performcollage of an image of another person and an image of the user to createa new image or video. This enables sharing of a new video work, such assharing the new image or video with only persons in the community.Moreover, the video work can also be used for a game of augmentedreality or the like by inserting a computer-graphics (CG) character inthis editing.

Moreover, since the system enables sequential output ofthree-dimensional model data, a 3D printer or the like that the facilityhas can output a three-dimensional object, based on thethree-dimensional model data in a characteristic scene such as a goalscene. This also enables sale after the game of an object based on thescene during the game as a souvenir such as a key ring, or distributionafter the game of such an object to participating users. Of course, thisalso enables printing of an image captured from the best viewpoint as anordinary photograph.

Variation 16

A center connected to the system can use the above-described system tomanage a rough state of the overall region, for example, from a video ofa vehicle-mounted camera of the police and a wearable camera of a policeofficer, and the like.

During ordinary patrol, still images are transmitted and received, forexample, every several minutes. Moreover, the center identifies a regionin which crime is highly likely to occur, based on a criminal mapprepared based on a result of analysis using past criminal data or thelike. Alternatively, the center keeps regional data related to a crimerate identified in this manner. In a region with the identifiedhigh-crime-rate, high frequency of transmission and reception of imagesmay be set, or a change of images to moving images may be made.Moreover, when an incident occurs, moving images or three-dimensionalreconfiguration data using SfM may be used. Moreover, the center or eachterminal can compensate the image or virtual space by concurrently usinginformation from other sensors such as a depth sensor and a thermalsensor, and accordingly the police officer can understand the situationwith better accuracy.

Moreover, the center can use the three-dimensional reconfiguration datato feed back information of the object to the plurality of terminals.This enables each individual person having a terminal to keep track ofthe object.

Moreover, in these years, capturing has been performed from the air byan apparatus that can fly such as a quadcopter and a drone, for purposesof investigation of buildings or environment, capturing with realismsuch as sports or the like. While blur of images is likely to become aproblem in capturing by such an autonomous moving apparatus, SfM cancreate three dimensions while compensating the blur with a position andan inclination. This can realize improvement in image quality andimprovement in restoration accuracy of space.

Moreover, installation of a vehicle-mounted camera that captures anoutside of a car is mandatory in some countries. In such avehicle-mounted camera, weather and a road surface state in a directionof a destination, traffic congestion level and the like can beunderstood with better accuracy by using three-dimensional data modeledfrom a plurality of images.

Variation 17

The above-described system may also be applied to a system that performsdistance measurement or modeling of a building or equipment by using aplurality of cameras, for example.

Here, for example, in a case of capturing an image of a building fromabove using one drone, and performing distance measurement or modelingof the building, there is an issue in that an image of a mobile objectmay be captured by the camera during distance measurement, therebyreducing the accuracy of distance measurement. There is also an issue inthat distance measurement and modeling cannot be performed with respectto a mobile object.

Meanwhile, by using a plurality of cameras (fixed cameras, smartphones,wearable cameras, drones, etc.) as described above, distance measurementand modeling of a building may be performed with stable accuracyregardless of presence or absence of a mobile object. Also, distancemeasurement and modeling may be performed with respect to a mobileobject.

Specifically, for example, at a construction site, a camera is attachedto a helmet or the like of a worker. This allows distance measurement ofthe building to be performed in parallel to the work of the worker.Also, efficiency of work may be increased, and mistakes may beprevented. Furthermore, modeling of the building may be performed byusing a video captured by the camera worn by the worker. Moreover, amanager at a remote location may check the progress by looking at amodeled building.

Moreover, this system may be used for inspection of equipment thatcannot be stopped, such as a machine at a factory or a power station.Also, this system can be used to inspect opening/closing of a bridge ora dam, or to inspect an abnormality in the operation of a ride in anamusement park, for example.

Moreover, by monitoring the level of traffic jam or the amount oftraffic on a road by this system, a map indicating the level of trafficjam or the amount of traffic on the road in each time zone may becreated.

Embodiment 6

The processing described in each of the above-described embodiments canbe carried out easily in a standalone computer system by recording aprogram for implementing the configuration of the image processingmethod described in each embodiment on a storage medium. The storagemedium may be any type of medium capable of storing the program, such asa magnetic disk, an optical disc, a magneto-optical disk, an integratedcircuit (IC) card, and a semiconductor memory.

Here, application examples of the image processing method described ineach of the embodiments and the systems using the application exampleswill be further described. The systems include an apparatus that usesthe image processing method. A change in other configurations of thesystems can be made appropriately in accordance with the circumstances.

FIG. 39 is a diagram illustrating an overall configuration of contentproviding system ex200 that implements content distribution services. Anarea in which communication services are provided is divided with adesired size. Base stations ex206, ex207, ex208, ex209, and ex210 whichare fixed wireless stations are installed in respective cells.

In content providing system ex200, various devices such as computerex211, personal digital assistant (PDA) ex212, camera ex213, smartphoneex214, and game machine ex215 are connected to Internet ex201 viaInternet service provider ex202, wide area network (WAN) ex204, and basestations ex206 to ex210.

However, the configuration of content providing system ex200 is notlimited to the configuration illustrated in FIG. 39, and any elementsmay be combined and connected. Moreover, each device may be connecteddirectly to telephone lines, cable TV, or WAN ex204 such as opticalcommunication, instead of via base stations ex206 to ex210 which arefixed wireless stations. Alternatively, each device may beinterconnected directly via near field communication or the like.

Camera ex213 is a device capable of capturing moving images, such as adigital camcorder. Camera ex216 is a device capable of capturing stillimages and moving images, such as a digital camera. Moreover, smartphoneex214 is, for example, a smartphone conforming to a global system formobile communication (GSM) (registered trademark) scheme, a codedivision multiple access (CDMA) scheme, a wideband-code divisionmultiple access (W-CDMA) scheme, an long term evolution (LTE) scheme, anhigh speed packet access (HSPA) scheme, or a communication scheme usinghigh-frequency bands, or a personal handyphone system (PHS), andsmartphone ex214 may be any of them.

In content providing system ex200, camera ex213 or the like is connectedto streaming server ex203 via base station ex209 and WAN ex204.Accordingly, live streaming or the like becomes possible. In the livestreaming, coding processing is performed on content (for example, avideo of a music event) captured by the user using camera ex213 and theresulting content is transmitted to streaming server ex203. Meanwhile,streaming server ex203 perform stream distribution of content datatransmitted to a client that has made a request. Examples of the clientinclude computer ex211, PDA ex212, camera ex213, smartphone ex214, andgame machine ex215 capable of decoding the data that has undergone thecoding processing. Each device that has received the distributed dataperforms decoding processing on the received data to reproduce the data.

Note that the coding processing of the captured video may be performedby camera ex213, or may be performed by streaming server ex203 thatperforms data transmission processing, or camera ex213 and streamingserver ex203 may share tasks of the coding processing of the capturedvideo with each other. Similarly, the decoding processing of thedistributed data may be performed by the client, or may be performed bystreaming server ex203, or the client and streaming server ex203 mayshare tasks of the decoding processing of the captured video with eachother. Moreover, in addition to still and/or moving image data capturedby camera ex213, still and/or moving image data captured by camera ex216may be transmitted to streaming server ex203 via computer ex211. In thiscase, the coding processing may be performed by any of camera ex216,computer ex211, and streaming server ex203, or camera ex216, computerex211, and streaming server ex203 may share tasks of the codingprocessing with each other. Further, regarding display of the decodedimage, a plurality of devices connected to the system may cooperate todisplay an identical image, or a device having a large display unit maydisplay the entire image and a device such as smartphone ex214 mayenlarge and display some area of the image.

Moreover, the coding processing and the decoding processing areperformed in general by LSI ex500 in computer ex211 or each device. LSIex500 may include a single chip or a plurality of chips. Note thatsoftware for coding/decoding a moving image may be recorded on anyrecording medium (such as a CD-ROM, a flexible disk, and a hard disk)that is readable by computer ex211 or the like, and the codingprocessing and the decoding processing may be performed using thesoftware. Further, in the case where smartphone ex214 is equipped with acamera, moving image data acquired by the camera may be transmitted.This moving image data is data that has been coded by LSI ex500 insmartphone ex214.

Moreover, streaming server ex203 may be a plurality of servers or aplurality of computers that processes, records, and distributes data.

In the above-described manner, content providing system ex200 enablesthe client to receive and reproduce coded data. Thus, content providingsystem ex200 enables the client to receive, decode, and reproduce inreal time information transmitted by a user, and enables even a userhaving no special right or equipment to implement personal broadcasting.

Note that in addition to the example of content providing system ex200,each of the above-described embodiments may also be applied to digitalbroadcasting system ex300, as illustrated in FIG. 40. Specifically,broadcasting station ex301 transmits multiplexed data obtained bymultiplexing video data with music data or the like via a radio wave tocommunication or satellite ex302. This video data is data coded by themoving image coding method described in each of the above-describedembodiments. Broadcasting satellite ex302 that has received this datatransmits a broadcasting radio wave, and home antenna ex304 capable ofreceiving satellite broadcasting receives this radio wave. An apparatussuch as television (receiver) ex400 or set top box (STB) ex317 decodesand reproduces the received multiplexed data.

Moreover, the moving image decoding apparatus or the moving image codingapparatus described in each of the above-described embodiments can beimplemented in reader/recorder ex318 that reads and decodes themultiplexed data recorded on recording medium ex315 such as a digitalversatile disc (DVD) and a blu-ray disc (BD) or memory ex316 such as ansecured digital (SD), or that codes a video signal and furthermultiplexes the video signal with a music signal depending oncircumstances, and writes the resulting signal on recording medium ex315or memory ex316. In this case, monitor ex319 may display the reproducedvideo signal, and another apparatus or system can reproduce the videosignal by using recording medium ex315 or memory ex316 having themultiplexed data recorded thereon. Moreover, the moving image decodingapparatus may be implemented in set top box ex317 connected to cableex303 for a community antenna television system (CATV) or antenna ex304for satellite/terrestrial broadcasting, and monitor ex319 of thetelevision may display the video signal. At this time, the moving imagedecoding apparatus may be incorporated into the television instead ofthe set top box.

FIG. 41 is a diagram illustrating smartphone ex214. Moreover, FIG. 42 isa diagram illustrating a configuration example of smartphone ex214.Smartphone ex214 includes antenna ex450 that transmits and receives aradio wave to and from base station ex210, camera ex465 capable ofcapturing a video and a still image, and display unit ex458 such as aliquid crystal display that displays the video captured by camera ex465and data obtained by decoding a video or the like received on antennaex450. Smartphone ex214 further includes operation unit ex466 which is atouch panel or the like, audio outputter ex457 such as a speaker foroutputting audio, audio inputter ex456 such as a microphone forinputting audio, memory unit ex467 capable of storing coded data ordecoded data of a captured video, a captured still image, recordedaudio, a received video, a received still image, or a received email,memory ex316 illustrated in FIG. 40, or slot ex464 which is an interfaceto SIM ex468 for identifying a user and for authentication of access tovarious types of data including a network.

In smartphone ex214, power supply circuit ex461, operation inputcontroller ex462, video signal processor ex455, camera interface ex463,liquid crystal display (LCD) controller ex459, modulator/demodulatorex452, multiplexer/demultiplexer ex453, audio signal processor ex454,slot ex464, and memory unit ex467 are connected via bus ex470 to maincontroller ex460 that comprehensively controls display unit ex458,operation unit ex466 and the like, respectively.

When an on-hook/power key is turned on by a user operation, power supplycircuit ex461 supplies electric power to each unit from a battery pack,and accordingly activates smartphone ex214 into an operable state.

In smartphone ex214 based on control of main controller ex460 thatincludes a CPU, a ROM, a RAM and the like, audio signal processor ex454converts an audio signal recorded with audio inputter ex456 in a voicecall mode into a digital audio signal, and modulator/demodulator ex452performs spread spectrum processing on this digital audio signal, andtransmitter/receiver ex451 performs digital-to-analog conversionprocessing and frequency conversion processing on this signal and thentransmits the resulting signal via antenna ex450. Moreover, smartphoneex214, amplifies reception data received via antenna ex450 in the voicecall mode and performs frequency conversion processing andanalog-to-digital conversion processing on the data, andmodulator/demodulator ex452 performs spread spectrum processing on theresulting signal, and audio signal processor ex454 converts theresulting signal into an analog audio signal, and then audio outputterex457 outputs the analog audio signal.

In the case where an email is transmitted in a data communication mode,text data of the email input by operation of operation unit ex466 or thelike of a body is sent to main controller ex460 via operation inputcontroller ex462. In main controller ex460 modulator/demodulator ex452performs spread spectrum processing on the text data, andtransmitter/receiver ex451 performs digital-to-analog conversionprocessing and frequency conversion processing on the text data and thentransmits the resulting text data to base station ex210 via antennaex450. In the case of receiving an email, substantially the oppositeprocessing is performed on the received data, and the resulting data isoutput to display unit ex458.

In the case where a video, a still image, or a combination of a videoand audio are transmitted in the data communication mode, video signalprocessor ex455 compresses and codes a video signal supplied from cameraex465 by the moving image coding method described in each of the aboveembodiments, and sends the coded video data to multiplexer/demultiplexerex453. Moreover, audio signal processor ex454 codes an audio signalrecorded with audio inputter ex456 while the video, the still image, orthe like is being captured by camera ex465, and sends the coded audiodata to multiplexer/demultiplexer ex453.

Multiplexer/demultiplexer ex453 multiplexes the coded video datasupplied from video signal processor ex455 and the coded audio datasupplied from audio signal processor ex454 by a predetermined scheme.Modulator/demodulator (modulation/demodulation circuit) ex452 performsspread spectrum processing on the resulting multiplexed data.Transmitter/receiver ex451 performs digital-to-analog conversionprocessing and frequency conversion processing on the multiplexed data,and then transmits the resulting data via antenna ex450.

In the case of receiving data of a moving image file linked to a websiteor the like in the data communication mode, or in the case of receivingan email having a video or audio attached thereto,multiplexer/demultiplexer ex453 demultiplexes multiplexed data into abitstream of video data and a bitstream of audio data in order to decodethe multiplexed data received via antenna ex450.Multiplexer/demultiplexer ex453 supplies the coded video data to videosignal processor ex455 and the coded audio data to audio signalprocessor ex454 via synchronization bus ex470. Video signal processorex455 decodes the video signal by a moving image decoding methodcorresponding to the moving image coding method described in each of theabove embodiments. Display unit ex458 displays via LCD controller ex459a video or still image in the moving image file linked to the website.Moreover, audio signal processor ex454 decodes the audio signal, andaudio outputter ex457 outputs audio.

Moreover, like television ex400, three implementation forms of aterminal such as smartphone ex214, that is, a transmission/receptionterminal including both an encoder and a decoder, a transmissionterminal including only an encoder, and a reception terminal includingonly a decoder, are conceivable. Further, digital broadcasting systemex300 in which multiplexed data obtained by multiplexing video data withmusic data or the like is received and transmitted is described above;however, the multiplexed data may be data obtained by multiplexing textdata or the like related to the video other than audio data, or may bevideo data as is instead of the multiplexed data.

Moreover, the present disclosure is not limited to the above-describedexemplary embodiments, and various variations or modifications can bemade without departing from the scope of the present disclosure.

Although only some exemplary embodiments of the present disclosure havebeen described in detail above, those skilled in the art will readilyappreciate that many modifications are possible in the exemplaryembodiments without materially departing from the novel teachings andadvantages of the present disclosure. Accordingly, all suchmodifications are intended to be included within the scope of thepresent disclosure.

INDUSTRIAL APPLICABILITY

The present disclosure is applicable to a three-dimensional informationprocessing device.

What is claimed is:
 1. A three-dimensional information processingmethod, comprising: obtaining, via a communication channel, map datathat includes first three-dimensional position information; generatingsecond three-dimensional position information from information detectedby a sensor; judging whether the first three-dimensional positioninformation has been obtained via the communication channel; when thefirst three-dimensional position information is judged to have beenobtained via the communication channel, estimating a location of amobile object having the sensor using the first three-dimensionalposition information and the second three-dimensional positioninformation; and when the first three-dimensional position informationis judged to not have been obtained via the communication channel, (i)obtaining, via the communication channel, third three-dimensionalposition information having a narrower range than a range of the firstthree-dimensional position information and (ii) estimating the locationof the mobile object having the sensor using the secondthree-dimensional position information and the third three-dimensionalposition information.
 2. The three-dimensional information processingmethod according to claim 1, wherein the first three-dimensionalposition information includes a plurality of random access units, eachof random access units being individually decodable, and each of therandom access units including at least one subspace havingthree-dimensional coordinates information and serving as a unit in whichthe random access unit is encoded.
 3. The three-dimensional informationprocessing method according to claim 1, wherein the firstthree-dimensional position information is data obtained by encodingkeypoints, each of which has an amount of a three-dimensional featuregreater than or equal to a predetermined threshold.
 4. Thethree-dimensional information processing method according to claim 1,further comprising: judging whether data of the first three-dimensionalposition information is corrupted; when the data of the firstthree-dimensional position information is judged to not be corrupted,estimating a location of a mobile object having the sensor using thefirst three-dimensional position information and the secondthree-dimensional position information; and when the data of the firstthree-dimensional position information is judged to be corrupted, (i)identifying a corrupted portion of the data of the firstthree-dimensional position information, (ii) updating, via thecommunication channel, the first three-dimensional position informationsuch that the data of the first three-dimensional position informationdoes not include the identified corrupted portion, and (ii) estimatingthe location of the mobile object having the sensor using the updatedfirst three-dimensional position information and the secondthree-dimensional position information.
 5. The three-dimensionalinformation processing method according to claim 1, further comprisingjudging whether a data accuracy of the second three-dimensional positioninformation is higher than or equal to a reference value; and when thedata accuracy of the second three-dimensional position information isjudged to be higher than or equal to the reference value, estimating alocation of a mobile object having the sensor using the firstthree-dimensional position information and the second three-dimensionalposition information.
 6. The three-dimensional information processingmethod according to claim 5, further comprising when the data accuracyof the second three-dimensional position information is not judged to behigher than or equal to the reference value, generating fourththree-dimensional position information from information detected by analternative sensor different from the sensor and (ii) estimating thelocation of the mobile object having the sensor using the firstthree-dimensional position information and the fourth three-dimensionalposition information.
 7. The three-dimensional information processingmethod according to claim 5, further comprising: performing automaticoperation of the mobile object by use of the location having beenestimated; and when the data accuracy of the second three-dimensionalposition information is not judged to be higher than or equal to thereference value, switching a mode of the automatic operation to another.8. The three-dimensional information processing method according toclaim 5, further comprising when the data accuracy of the secondthree-dimensional position information is not judged to be higher thanor equal to the reference value, calibrating an operation of the sensor.9. A three-dimensional information processing method, comprising:obtaining, via a communication channel, map data that includes firstthree-dimensional position information; generating secondthree-dimensional position information from information detected by asensor; predicting whether the mobile object will enter an area in whichthe first three-dimensional position information is more difficult toobtain via the communication channel while the mobile object is in thearea than while the mobile object is not in the area; when it ispredicted that the mobile object will not enter the area in which thefirst three-dimensional position information is more difficult to obtainvia the communication channel while the mobile object is in the areathan while the mobile object is not in the area, estimating a locationof a mobile object having the sensor using the first three-dimensionalposition information and the second three-dimensional positioninformation; and when it is predicted that the mobile object will enterthe area in which the first three-dimensional position information ismore difficult to obtain via the communication channel while the mobileobject is in the area than while the mobile object is not in the area,(i) obtaining, via the communication channel, third three-dimensionalposition information having a narrower range than a range of the firstthree-dimensional position information and (ii) estimating the locationof the mobile object having the sensor using the secondthree-dimensional position information and the third three-dimensionalposition information.
 10. A three-dimensional information processingmethod, comprising: obtaining, via a communication channel, map datathat includes first three-dimensional position information; generatingsecond three-dimensional position information from information detectedby a sensor; judging whether the first three-dimensional positioninformation has been obtained via the communication channel; when thefirst three-dimensional position information is judged to have beenobtained via the communication channel, estimating a location of amobile object having the sensor using the first three-dimensionalposition information and the second three-dimensional positioninformation; and when the first three-dimensional position informationis judged to not have been obtained via the communication channel, (i)obtaining, via the communication channel, map data includingtwo-dimensional position information and (ii) estimating the location ofthe mobile object having the sensor using the two-dimensional positioninformation and the second three-dimensional position information. 11.The three-dimensional information processing method according to claim10, further comprising: performing automatic operation of the mobileobject by use of the location having been estimated; and when thelocation of the mobile object is estimated using the two-dimensionalposition information and the second three-dimensional positioninformation, judging whether to perform the automatic operation of themobile object by use of the location of the mobile object, based on anenvironment in which the mobile object is traveling.
 12. Thethree-dimensional information processing method according to claim 10,further comprising: performing automatic operation of the mobile objectby use of the location having been estimated; and switching a mode ofthe automatic operation to another based on an environment in which themobile object is traveling.
 13. The three-dimensional informationprocessing method according to claim 10, wherein the firstthree-dimensional position information includes a plurality of randomaccess units, each of the random access units being individuallydecodable, and each of the random access units including at least onesubspace having three-dimensional coordinates information and serving asa unit in which the random access unit is encoded.
 14. Thethree-dimensional information processing method according to claim 10,wherein the first three-dimensional position information is dataobtained by encoding keypoints, each of which has an amount of athree-dimensional feature greater than or equal to a predeterminedthreshold.
 15. The three-dimensional information processing methodaccording to claim 10, further comprising: judging whether data of thefirst three-dimensional position information is corrupted; when the dataof the first three-dimensional position information is judged to not becorrupted, estimating a location of a mobile object having the sensorusing the first three-dimensional position information and the secondthree-dimensional position information; and when the data of the firstthree-dimensional position information is judged to be corrupted, (i)identifying a corrupted portion of the data of the firstthree-dimensional position information, (ii) updating, via thecommunication channel, the first three-dimensional position informationsuch that the data of the first three-dimensional position informationdoes not include the identified corrupted portion, and (ii) estimatingthe location of the mobile object having the sensor using the updatedfirst three-dimensional position information and the secondthree-dimensional position information.
 16. The three-dimensionalinformation processing method according to claim 10, further comprisingjudging whether a data accuracy of the second three-dimensional positioninformation is higher than or equal to a reference value; and when thedata accuracy of the second three-dimensional position information isjudged to be higher than or equal to the reference value, estimating alocation of a mobile object having the sensor using the firstthree-dimensional position information and the second three-dimensionalposition information.
 17. The three-dimensional information processingmethod according to claim 16, further comprising when the data accuracyof the second three-dimensional position information is not judged to behigher than or equal to the reference value, generating fourththree-dimensional position information from information detected by analternative sensor different from the sensor and (ii) estimating thelocation of the mobile object having the sensor using the firstthree-dimensional position information and the fourth three-dimensionalposition information.
 18. The three-dimensional information processingmethod according to claim 16, further comprising: performing automaticoperation of the mobile object by use of the location having beenestimated; and when the data accuracy of the second three-dimensionalposition information is not judged to be higher than or equal to thereference value, switching a mode of the automatic operation to anothermode.
 19. The three-dimensional information processing method accordingto claim 16, further comprising when the data accuracy of the secondthree-dimensional position information is not judged to be higher thanor equal to the reference value, calibrating an operation of the sensor.20. A three-dimensional information processing device, comprising: anobtainer that obtains, via a communication channel, map data thatincludes first three-dimensional position information; a generator thatgenerates second three-dimensional position information from informationdetected by a sensor; a judgment unit that judges whether the firstthree-dimensional position information has been obtained via thecommunication channel; and an operation controller that when the firstthree-dimensional position information is judged to have been obtainedvia the communication channel, estimates a location of a mobile objecthaving the sensor using the first three-dimensional position informationand the second three-dimensional position information, and when thefirst three-dimensional position information is judged to not have beenobtained via the communication channel, (i) obtains, via thecommunication channel, third three-dimensional position informationhaving a narrower range than a range of the first three-dimensionalposition information and (ii) estimates the location of the mobileobject having the sensor using the second three-dimensional positioninformation and the third three-dimensional position information.